Skip to content

Instantly share code, notes, and snippets.

@mnowotka

mnowotka/mapping_fingerprint_data_into_2d.ipynb

Created May 2, 2014 13:58
Show Gist options
  • Save mnowotka/c21e0d91f80f2c14dd47 to your computer and use it in GitHub Desktop.
Save mnowotka/c21e0d91f80f2c14dd47 to your computer and use it in GitHub Desktop.
Download ZIP
Display the source blob
Display the rendered blob
Raw
mapping_fingerprint_data_into_2d.ipynb
{
"metadata": {
"name": "",
"signature": "sha256:a250cbab3a274f024d968f7f35b5b76a7cf041e298dd27f2579328693ce088f6"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Using open tools and ChEMBL webservices to perform some non-trivial task\n",
"This is slightly modified version of this article by Greg Landrum http://rdkit.blogspot.co.uk/search?updated-max=2014-02-02T20:05:00-08:00&max-results=7&start=7&by-date=false, which in turn is based on this notebook http://nbviewer.ipython.org/gist/madgpap/8538507 from George Papadatos.\n",
"\n",
"Scikit-learn makes it quite easy to apply multi-dimensional scaling (MDS) to either reduce the dimensionality of a dataset or to embed distance data into cartesian space. This enables one of the favorite activities of the cheminformatician: producing plots of where compounds land in an 2D space."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from chembl_webresource_client import *\n",
"import pandas as pd\n",
"from rdkit.Chem import PandasTools\n",
"from rdkit.Chem import AllChem as Chem\n",
"from rdkit.Chem import DataStructs\n",
"from sklearn import manifold"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 76
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Grab the data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I'm going to start with a larger dataset so that I can explore the impact of dataset size on the results. The analysis of George's results are below.\n",
"\n",
"I'll use the Dopamine D3 receptor as the target for this exercise. It's one of the targets we used in both the benchmarking and model fusion papers."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"targets = TargetResource()\n",
"target='CHEMBL234'\n",
"bio = targets.bioactivities(target)\n",
"data = pd.DataFrame(bio)\n",
"data.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>activity_comment</th>\n",
" <th>assay_chemblid</th>\n",
" <th>assay_description</th>\n",
" <th>assay_type</th>\n",
" <th>bioactivity_type</th>\n",
" <th>ingredient_cmpd_chemblid</th>\n",
" <th>name_in_reference</th>\n",
" <th>operator</th>\n",
" <th>organism</th>\n",
" <th>parent_cmpd_chemblid</th>\n",
" <th>reference</th>\n",
" <th>target_chemblid</th>\n",
" <th>target_confidence</th>\n",
" <th>target_name</th>\n",
" <th>units</th>\n",
" <th>value</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> Unspecified</td>\n",
" <td> CHEMBL838684</td>\n",
" <td> Binding affinity for human dopamine D3 receptor</td>\n",
" <td> B</td>\n",
" <td> Ki</td>\n",
" <td> CHEMBL367720</td>\n",
" <td> 28</td>\n",
" <td> =</td>\n",
" <td> Homo sapiens</td>\n",
" <td> CHEMBL367720</td>\n",
" <td> J. Med. Chem., (2005) 48:3:839</td>\n",
" <td> CHEMBL234</td>\n",
" <td> 7</td>\n",
" <td> Dopamine D3 receptor</td>\n",
" <td> nM</td>\n",
" <td> 2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> Unspecified</td>\n",
" <td> CHEMBL669163</td>\n",
" <td> Binding affinity towards human cloned dopamine (hD3) receptor expressed in CHO cells using [3H]spiperone as radioligand</td>\n",
" <td> B</td>\n",
" <td> Ki</td>\n",
" <td> CHEMBL300571</td>\n",
" <td> 4</td>\n",
" <td> =</td>\n",
" <td> Homo sapiens</td>\n",
" <td> CHEMBL300571</td>\n",
" <td> Bioorg. Med. Chem. Lett., (1998) 8:3:295</td>\n",
" <td> CHEMBL234</td>\n",
" <td> 8</td>\n",
" <td> Dopamine D3 receptor</td>\n",
" <td> nM</td>\n",
" <td> 1.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> Unspecified</td>\n",
" <td> CHEMBL666966</td>\n",
" <td> Displacement of [3H]spiperone from human dopamine receptor subtype hD3 expressed in CHO cells</td>\n",
" <td> B</td>\n",
" <td> Ki</td>\n",
" <td> CHEMBL69356</td>\n",
" <td> 13</td>\n",
" <td> =</td>\n",
" <td> Homo sapiens</td>\n",
" <td> CHEMBL69356</td>\n",
" <td> Bioorg. Med. Chem. Lett., (1997) 7:17:2211</td>\n",
" <td> CHEMBL234</td>\n",
" <td> 7</td>\n",
" <td> Dopamine D3 receptor</td>\n",
" <td> nM</td>\n",
" <td> 1600</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> Unspecified</td>\n",
" <td> CHEMBL961810</td>\n",
" <td> Displacement of [125]IABN from human D3 receptor expressed in HEK293 cells</td>\n",
" <td> B</td>\n",
" <td> Ki</td>\n",
" <td> CHEMBL68740</td>\n",
" <td> 9</td>\n",
" <td> =</td>\n",
" <td> Homo sapiens</td>\n",
" <td> CHEMBL68740</td>\n",
" <td> J. Med. Chem., (2009) 52:8:2559</td>\n",
" <td> CHEMBL234</td>\n",
" <td> 9</td>\n",
" <td> Dopamine D3 receptor</td>\n",
" <td> nM</td>\n",
" <td> 0.52</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> Unspecified</td>\n",
" <td> CHEMBL670425</td>\n",
" <td> Antagonistic activity of quinpirole stimulation of mitogenesis in human Dopamine receptor D3 transfected CHO cells</td>\n",
" <td> F</td>\n",
" <td> IC50</td>\n",
" <td> CHEMBL68740</td>\n",
" <td> 23</td>\n",
" <td> =</td>\n",
" <td> Homo sapiens</td>\n",
" <td> CHEMBL68740</td>\n",
" <td> Bioorg. Med. Chem. Lett., (2003) 13:13:2179</td>\n",
" <td> CHEMBL234</td>\n",
" <td> 8</td>\n",
" <td> Dopamine D3 receptor</td>\n",
" <td> nM</td>\n",
" <td> 52.4</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 16 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 53,
"text": [
" activity_comment assay_chemblid assay_description assay_type bioactivity_type ingredient_cmpd_chemblid name_in_reference operator organism parent_cmpd_chemblid reference target_chemblid target_confidence target_name units value\n",
"0 Unspecified CHEMBL838684 Binding affinity for human dopamine D3 receptor B Ki CHEMBL367720 28 = Homo sapiens CHEMBL367720 J. Med. Chem., (2005) 48:3:839 CHEMBL234 7 Dopamine D3 receptor nM 2\n",
"1 Unspecified CHEMBL669163 Binding affinity towards human cloned dopamine (hD3) receptor expressed in CHO cells using [3H]spiperone as radioligand B Ki CHEMBL300571 4 = Homo sapiens CHEMBL300571 Bioorg. Med. Chem. Lett., (1998) 8:3:295 CHEMBL234 8 Dopamine D3 receptor nM 1.1\n",
"2 Unspecified CHEMBL666966 Displacement of [3H]spiperone from human dopamine receptor subtype hD3 expressed in CHO cells B Ki CHEMBL69356 13 = Homo sapiens CHEMBL69356 Bioorg. Med. Chem. Lett., (1997) 7:17:2211 CHEMBL234 7 Dopamine D3 receptor nM 1600\n",
"3 Unspecified CHEMBL961810 Displacement of [125]IABN from human D3 receptor expressed in HEK293 cells B Ki CHEMBL68740 9 = Homo sapiens CHEMBL68740 J. Med. Chem., (2009) 52:8:2559 CHEMBL234 9 Dopamine D3 receptor nM 0.52\n",
"4 Unspecified CHEMBL670425 Antagonistic activity of quinpirole stimulation of mitogenesis in human Dopamine receptor D3 transfected CHO cells F IC50 CHEMBL68740 23 = Homo sapiens CHEMBL68740 Bioorg. Med. Chem. Lett., (2003) 13:13:2179 CHEMBL234 8 Dopamine D3 receptor nM 52.4\n",
"\n",
"[5 rows x 16 columns]"
]
}
],
"prompt_number": 53
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 54,
"text": [
"(6714, 16)"
]
}
],
"prompt_number": 54
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Remove duplicates"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data = data.drop_duplicates(['parent_cmpd_chemblid'])\n",
"data.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 55,
"text": [
"(4399, 16)"
]
}
],
"prompt_number": 55
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Remove assays with too many or too few compounds"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"assays = data[['assay_chemblid','target_chemblid']].groupby('assay_chemblid').count()\n",
"print assays.shape\n",
"assays.head(5)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(465, 2)\n"
]
},
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>assay_chemblid</th>\n",
" <th>target_chemblid</th>\n",
" </tr>\n",
" <tr>\n",
" <th>assay_chemblid</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>CHEMBL1030601</th>\n",
" <td> 9</td>\n",
" <td> 9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHEMBL1030747</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHEMBL1031083</th>\n",
" <td> 5</td>\n",
" <td> 5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHEMBL1031401</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHEMBL1032031</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 2 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 56,
"text": [
" assay_chemblid target_chemblid\n",
"assay_chemblid \n",
"CHEMBL1030601 9 9\n",
"CHEMBL1030747 1 1\n",
"CHEMBL1031083 5 5\n",
"CHEMBL1031401 1 1\n",
"CHEMBL1032031 1 1\n",
"\n",
"[5 rows x 2 columns]"
]
}
],
"prompt_number": 56
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"assays.assay_chemblid.hist(bins=20)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 57,
"text": [
"<matplotlib.axes.AxesSubplot at 0x6076ed0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD9CAYAAAC/fMwDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x6ba9610>"
]
}
],
"prompt_number": 57
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"goodassays = assays.ix[(assays.assay_chemblid >= 10)&(assays.assay_chemblid <= 30)]\n",
"print goodassays.shape\n",
"goodassays.assay_chemblid.hist(bins=20)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(108, 2)\n"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 58,
"text": [
"<matplotlib.axes.AxesSubplot at 0x605a690>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAXEAAAD9CAYAAABKgkezAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x69d34d0>"
]
}
],
"prompt_number": 58
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data2 = data.ix[data.assay_chemblid.isin(list(goodassays.index))]\n",
"data2.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 59,
"text": [
"(1782, 16)"
]
}
],
"prompt_number": 59
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Now get the SMILES"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"compounds = CompoundResource()\n",
"cs = compounds.get(list(data2['parent_cmpd_chemblid']))\n",
"smiles = pd.Series(map(lambda x: x['smiles'], cs), index=data2.index)\n",
"data2['SMILES'] = smiles"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 61
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"PandasTools.AddMoleculeColumnToFrame(data2, smilesCol = 'SMILES',includeFingerprints=True)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 62
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's start by looking at assays that have between 10 and 12 compounds:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"assays = data2[['assay_chemblid','target_chemblid']].groupby('assay_chemblid').count()\n",
"print assays.shape\n",
"goodassays = assays.ix[(assays.assay_chemblid >= 10)&(assays.assay_chemblid <= 12)]\n",
"subset = data2.ix[data.assay_chemblid.isin(list(goodassays.index))]\n",
"print subset.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(108, 2)\n",
"(305, 18)\n"
]
}
],
"prompt_number": 63
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mols = subset[['parent_cmpd_chemblid','name_in_reference','SMILES', 'ROMol', 'assay_chemblid']]\n",
"mols.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 64,
"text": [
"(305, 5)"
]
}
],
"prompt_number": 64
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mols.head(5)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>parent_cmpd_chemblid</th>\n",
" <th>name_in_reference</th>\n",
" <th>SMILES</th>\n",
" <th>ROMol</th>\n",
" <th>assay_chemblid</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>11</th>\n",
" <td> CHEMBL97333</td>\n",
" <td> 15d</td>\n",
" <td> CN1CCC(CCN2CCC(CC2)c3cn(c4ccc(F)cc4)c5ccc(cc35)c6ncn(C)n6)C1=O</td>\n",
" <td> <img src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
" <td> CHEMBL674985</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td> CHEMBL344270</td>\n",
" <td> 3c</td>\n",
" <td> Clc1ccc(cc1Cl)N2CCN(Cc3c[nH]c4ccc(cc34)C#N)CC2</td>\n",
" <td> <img src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
" <td> CHEMBL675671</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td> CHEMBL147829</td>\n",
" <td> 3</td>\n",
" <td> OC1(Cc2ccc(Cl)cc2)CCN(CCCC(=O)c3ccc(F)cc3)CC1</td>\n",
" <td> <img src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
" <td> CHEMBL671515</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td> CHEMBL196598</td>\n",
" <td> 6f</td>\n",
" <td> COc1ccc(NC(=O)N2CCN(CC2)c3ccc(cc3)C(F)(F)F)cc1N4CCN(C)CC4</td>\n",
" <td> <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAASwAAAEsCAYAAAB5fY51AAAeeUlEQVR4nO3deVzU1d4H8I+yuYEMZm43l6CnDHC5bvnk1SdzyS64tAKZmbkEmXn1phYmmSKapaaWXdMkvallLnVN0VxwyRDCFKFUxAW5piYMgwgM2/f5Y2SuKMr2m+XM/bxfr3k5jnDOd0o/nDO/8zunjogIiIgUUNfWBRARVRUDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCISBkMLCJSBgOLiJTBwCIiZTCwiEgZDCwiUgYDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCISBkMLCJSBgOLiJTBwCIiZTCwiEgZDCwiUgYDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCISBkMLCJSBgOLiJTBwCIiZTCwiEgZDCwiUgYDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCISBkMLCJSBgOLiJTBwCIiZTCwiEgZDCwiUgYDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCISBkMLCJSBgOLiJTBwCIiZTCwiEgZDCwiUgYDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCISBkMLCJSBgOLiJTBwCIiZTCwiEgZDCwiUgYDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCISBkMLCJSBgOLiJTBwCIiZTCwiEgZDCwiUgYDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCISBkMLCJSBgOLiJTBwCIiZTCwiEgZDCwiUgYDi4iUwcAiImUwsIhIGQwsIlIGA4uIlMHAIiJlMLCI6I5SU1NtXUI5DCwiqtCGDRvQpUsX6PV6W5dixsAiottkZGRg7NixiIqKgk6ns3U5ZnVERGxdBBHZl8DAQBQWFiImJgZ16tSxdTlmzrYugIjsS3R0NPbt24fjx4/bVVgBnBIS0U0uXQK+/vocoqLmok2bNrYu5zacEhIRAEAEGDAAcHYGtm0D7GxwBYBTQiK6YeVKIDEROH7cPsMKYGAREYDz54HJk4GFC4FWrWxdzZ1xSkhEePJJoLgY2LHDfkdXAEdYRARgzBigSxf7DiuAIywiUgiXNRCRMjglJFLM5cuXcejQIeh0unIPd3f3Kn3/+vXAggVAfDywdSuQmwsEBVm4aI0wsIgU8ssvv2DIkCEoLS2FwWBAbm6u+c+cnZ3Rq9dT+P33r6DT4bZHp07A00+bvtbHB9i8GXBxsc37qCkGFpEi8vPzERISgiFDhmDJkiUAgKKiImRlZUGv10Ov1yM3tyGuXAH0+vKPjAygXr3/tBUUZBppBQfb6M3UEAOLSBEREREoKSnBvHnzzK+5uLigWbNmaNasWbXaqlsXeOYZU2gFBmpdqeXwQ3ciBRw4cACLFi1CdHQ0GjRooEmbw4YBdrY/X6W4rIHIzuXn56NTp0548sknsXDhQluXY1McYRHZufDwcABAZGSkjSuxPX6GRWTH9u3bh6VLl2Lfvn2aTQVVxhEWkZ3Kzc3Fyy+/jDfeeAM9e/a0WD+bNgEBARZrXlP8DIvITk2YMAF79uxBYmIi3NzcLNZPRoZpXda2bUDfvhbrRhMMLCI7FBsbi4EDB+Knn37Cn//8Z4v3FxYG/PYbsHevxbuqFQYWkZ25du0aOnTogODgYMyZM8cqfV64YBpl7dwJ9OljlS5rhIFFZGfCwsJw8OBBJCQkWHQqeKtRo4CrV0vw3XdOVuuzuvihO5EdiYmJwcqVK/HFF19YNawAIDz8OuLi/BAfH2/VfqvD4UZYO7Oy8K/MTLRwc0M/T0909/CwdUlEVZKdnQ0/Pz+MGjUK7733nk1qGDVqFC5evIiYmBib9F8Zhwws17p18X+enrYuhaha9uzZg4kTJ1p9KniztLQ0PPTQQ4iNjcWjjz5qkxruxiGnhBv/+ANz0tORYTTauhSiKmvSpAl+/fVXpNrwBj9vb28EBwcjKirKZjXcDUdYRHZkyJAh8PDwwJo1a2xWQ0pKCrp27YozZ86gRYsWNqujIg45wiJSVXh4ONatW4dTp07ZrIbk5GS4uLigfv36NqvhThxuhEWkuoEDB+K+++7DihUrrN53RkYG/P39ERkZibCwMKv3XxkGVg3l5+dj2bJl2L17Nzw9Pc37apc9r+i1xo0b27psUkBs7AHMnp2H6OiB+NOfrNt3YGAgCgsLERMTgzp2eOYXA6uGJk+ejE2bNuGll16CwWBAdna2eZvasufZ2dm4du2a+Xvq1q17W5A1bdoU77//Pv5k7b+ZZNf69gUefBBYtsx6fa5evRrjx4/H8ePH0aZNG+t1XA0OF1h/FBXhp5wcDG7SxGJ9xMbGYsCAAThw4AB69Ohx168tLi4uF2K3Pj98+DCSkpJw8uRJuKh2IgBZzN69wMCBph1BrZEdGRkZ8PPzw9y5c/Hqq69avsMacrjA2m8wYM7584jp0MEi7Zfd5/X8889j7ty5KCkpgYjA2blmW4sVFBTA29sbERERGDt2rMbVVs+VK1dw4sQJeHl5QafTwcvLyy4/eP1v0acP0KEDcOO8CYsKCAhAcXExtm/fbpdTwTIOt4HfteJieDhZ7l6ot956C40aNcLMmTMBAPPnz8eBAwfw/fffV6ud4uJi5Ofnw93dHZMmTUJkZCRGjhwJV1dXS5Rdqbi4OIwcORIZGRm4fv26+fV69erBy8urXIiV/Xqn5/fff79d/6VXxfTppgMipk0DWrWyXD/R0dHYv38/jh8/bvf/3xxuhLXuyhXs0uux8sEHNW97586dCAgIwOHDh9G5c2ckJiaiZ8+e+P7779G/f/9qtfX888+jRYsWWLRoEfLy8tCuXTtERUVh1KhRmtddmdzcXHTo0AFPP/005s+fj8LCwrtOY2/+jO7W13JycjB58mS8//77Vn8fZgUFwKRJpkP3srOBiAjg/vttV08tzJ4NjB4NNG9umfYvXLgAf39/zJs3D+PGjbNMJ1oSB/OPf/9bJqamat5uTk6OtG3bVt566y0RETEajdKxY0d55ZVXatTezp07xc3NTTIyMkREZO7cueLt7S1FRUWa1VxV48ePF19fXykoKKh1W6mpqeLs7Czx8fEaVFZDixeLbNtmen71qsjw4barxY6VlpZK//795YknnpDS0lJbl1MlDhdY89PT5Z2zZzVvNzQ0VPz9/c3/qCMiIqR169ZiMBhq3Oajjz4qEydOFBGR3Nxcadq0qaxevVqTeqtqx44d4uLiIomJiZq1GRQUJMOGDdOsvWoLDRX5/ff//N6Wtdixzz//XDw9Pc0/NFXgcIE14/PPZcF332naZkxMjLi6usqRI0dERCQhIUFcXFxk165dtWr3+++/lwYNGsjly5dFRGTWrFnywAMPSHFxca1rrorr10UeeeQpmTx5sqbtpqSkiJOTkxw7dkzTdqvso4/Kj7BeeME2ddix9PR0ady4sSxfvtzWpVSLwwVWQECAREREaNZeTk6OtGnTRsLDw0VEJD8/Xx5++GEZO3asJu1369ZNpkyZIiIiBoNBdDqdrF27VpO2K/PGGyJduxZJfn6+5m0PGzZMgoKCNG+3SvLyRMaOFZkwwTQdtMBHBNa0bp1It26m5//6l+n3tVFaWir9+vVTaipYxi4Ca0dmpow/dUoiz5+Xw7WYYomYplmLFi3SqDKRcePGib+/vxiNRhERCQ8PF29vb8nNzdWk/S1btkjDhg3lypUrImKaarZv315KSko0af9Odu4UcXERuTFo1Fx8/FHp2fNb1bPCLqxbJxIcLLJpU/nAMhhEajIYX7Fiheh0OqWmgmXs4iqhljss+Pr6YurUqRgxYkSt29qxYwcGDx6Mw4cPo1OnToiPj0evXr0QExODvhodLyIi6Ny5MwICAjB79mwYDAa0bdsWy5cvx7PPPqtJH7fKzQX8/YGgIMCSu4gEBgI6HbB6teX6MPv5Z6BrVyt0ZH3r1wMNGph+DQ4Grl83/b9r0wZITwc8PEz/nb28TL/qdECrVtPg5lZqvqui7GE0GjF8+HAsWLAAr7zyiq3fWrXZTWCV7RI6olkz/MnNDbv0epSIwN3ZGe5OTvBwcoK7kxPcnZ3hcpe1Ii1btsTy5csRUMuD1nJyctChQwe8+OKLmDVrFgoKCtC5c2f07dsXH3/8ca3avtWGDRswevRonDt3DjqdDu+88w42b96MpKQk1K2r/YYaEyYAe/YAiYmAJfeJS0wEHnkESEkB/ud/LNcPdu8GBg0CkpMt3JFtrF8PNGoEFBYCGzeafhAEBQHnzwOZmYBef/vj+vVJuHz53+ZlJzc/ypad2Puaq4rYTWDdOsKalJaGs/n5uFZSgpySEpTeVOb9Bw7gx/nzK7zZeNmyZQgLC0OXLl0qXOhY1YWZ48aNQ1xcHBISEuDq6opp06Zh48aNOHr0KBo2bKjp+xcRdOjQAc888wwiIiKQlZWFtm3bYvXq1Rg6dKimfRUVAf36AZGRQK9emjZdoUGDgBYtgM8/t1AHej3g5weMGwfMmAGUlAD79wOPPWahDq2vLLD++legRw/TErOgIFtXZRt2G1i3yispMYdX5unTuHzmzG0LGDMzM/Hdd9/hgQceQEFBAfR6PbKysmC8aefRhg0bVrpa+9KlS4iMjMTBgwfRvXt3HDx4EH379sXevXsttm3s2rVrERYWhnPnzsHT0xPTpk3Dzp07kZiYqORPwjL79wP9+5vuiWvd2gIdjBwJ/PorcOgQ4OwMzJ0LfPQRcPo0oPEPFrI9uwgsrVy8eBGtWrXCxYsXy+2UeP36dXN4ZWVlmZ9X9FpWVhYyMzPRunVr7N+/HwCwePFinDx5UvOp4M1KSkrg6+uLESNG4O2338bVq1fRrl07rFu3rtbTW1vbuhV44glTnmhq82YgJAQ4cgRo3940B+3Z03SEcb9+GndGdsE2n/VbRnJysgCo9WX606dPi7Ozsxw8eFCjyqomOjpamjRpIjk5OSIiMnnyZOnSpUuNLz1rfTncnmRnZ8tXgYFSGBlpesFoFOnQQWT0aNsWpqHISJGFC21dhX1xqJuf9Xo96tevj3r16tWqHW9vb4SEhCAqKgpbt27VqLrKhYSEYO/evTAYDHB3d0dQUBC++eYb1KtX77arPTqdDj4+/VFa+pL5ylDZw8sLaNbM1KaPj2kg4mg710yYMAG/XbqEp6ZMMb0waxZgMAAffmjbwjQSHw+8+y5gp6dt2YzDBZZOp9OkrXfeeQft27dHQkICunXrpkmblXFxcUF0dDQA0wfxU6dOha+vL9auXVvh1R6j0RUpKbdfIcrPB15/Hfjf/zV9OFt2OdxRbNmyBV9//TWOHDkCZ2dnHDt2DBcOHcJfly1DHQc4h7KgAHjpJWDMGNNGfnQTWw/xtPTFF1+Ir6+vZu2FhITIkCFDNGuvOj755BPx8vKSixcvVvt78/NNi73XrTNNBTduFAkJse2UUKvpaVZWlrRo0UJmzZolIqY7D9q3by+hoaEaVWp7U6eK+PiIaLQ22aE41AirXu/eeKJjR83amz59Ovz9/ZGYmIguXbpo1m5l0tLS8Oabb2LZsmU1Ombp1hnxsGGmi2e2VtH0dP9+oH798lPauy09mzZtGpo2bYopN6aCM2fORFFREebPn2/h6q3j6NGrWLToHmzdyoucFXGoq4TLL17Eibw8LPDx0azN5557DqWlpfjmm280a/NuRASPP/44PD09sWnTJqv0aQ2Vrda+maenKbhatBiA+vXLr9bOzs5G06ZN8e677yIuLs7iy02syWg0omvXrggMnIQ5c162dTl2yaFGWDklJXDX+Np5REQEOnbsiOPHj8Pf31/TtivyySef4NixY0hOTrZ4X9ZWty7wzDOm0AoMNL12/rzp14pWa+v1z0KvzzJ/Znf27Fno9XrExsbi4MGDyM7OxqhRoxwirADTmYRGoxHTpz9v61Lsl42npJp658wZ+TA9XfN2rbXzQGpqqjRo0EDWrFlj8b6srezztNJS02dZtfk8LTMzU9zd3SUqKsq8BER1+/btExcXFzl06JCtS7FrDjUlnHj6NHwbNsQYjY/XPnr0KLp27YqjR4/Cz89P07bLlJaWonfv3mjWrBk2btxokT4A04Lwc+dM6y1V9vbbb2P79u04cuSIze4EyMzMRGhoKDZs2HDHpScVPcqW3pT93t3dHZ06dcLQoUPxoYMsy7AUhwqsUSdPYqBOh+fvvVfztgcPHozGjRtjzZo1mrcNAEuXLsV7772HlJQUNG3a1CJ9AMC6dUBoqCm0NNgco1JGo2VusM7MzES7du3wz3/+E4MHD9a+gyoYOnQo/vjjD8yfPx8Gg6FK++Dr9XoYDIZy7TRq1AjNmze3yH2qDse2AzxtHc/NlSuFhRZpOzExUZycnOTEiROat102Ffzyyy81b/tWxcUiDz4oMmeOxbsSEZGhQ0VmzrRM2xMnTpQ+fR6zTOOVWLt2rTRq1EjOnDlT7e8tLS2VzMxMOX36tPz888+yZMkScXJykpMnT1qgUsfiUCMsSxs0aBCaN2+OVatWAQCWLFmCN99887Yhf9lN1BU9vLy80LJlS3jeGN6UTQWbN29utSuRq1YBb75pGmU1amTZfiZOBJKSLHMY6MWLV9GjRwk+/7wZqnloUa1cunQJfn5+mDFjBiZMmAAAWLZsGbKysu7698DpLsfPPfHEE2jVqhVWrlxprbehJAZWNcTFxaF37944ceIE7r//fly6dAlpaWnmoX7ZTdQVPcr+zGg0YsGCBfjb3/4GwHRjdWRkJJKTky06FbxZUZHpGPTXXwdulKG59HTTJoEffGBasW0pkyaZPpeLi7NcH7caPHgwrl27ht27d5v3K5syZQqSkpJu+3tQWlpq/j4PD4/bguyzzz6DTqfDTz/9hD59+uDkyZNo166d9d6MYhwisG7eALCfpye6W/D2jP79+6Ndu3ZYvnx5jb4/Ly8PTk5OcHNzQ2pqKjp16oSVK1ciyMobHH322VV8++1sbNw4D24af8gkYtpSxtXVtHGCJV26ZDpycMsWYMAAy/YFAGvWrMFrr72GpKQktG3bttKvL/ts604/0CIiIsz3vj7++OPw8fHBP/7xDwu/C3U5TGBptcVyZfbs2YPg4GA8/vjj5X5Slm0geOtzjzuEZ0lJCXr37o2WLVtiw4YNFq/7VkajET4+Ppg6dSrGjx+vadtffXUUEyd2xE8/1UEV/k3X2oQJph2SDx2ybD8ZGRnw8/NDVFQUQkNDNW8/NjYWAwYMQGpqKtpYYg7tABwmsG7dYtmSYmNj8e23397xSlBubq75a+vWrVthkOXk5CA+Ph7Jyck1uv1GC0uWLMH777+P06dPazbKysjIgL+/Pz78cClGjXpBkzYrc/488PDDwC+/WHaH5ICAABQXF2P79u0WW0rRp08f+Pv7Y+nSpRZpX3UOE1jWGmFVRVFRUaWXt4uKivDaa6/BR8PbiKqroKAAPj4+CA8P12TEICLo168fGjdubPXbivR60+08lrJq1SpMmjQJycnJaNWqlcX62bVrFwICApCWlmbRfpRlk2uTGtuRmSl79Xpbl6GkhQsXSqtWreTnn3+W9PT0Wq0c//jjj2u8w4Q9O3/+vFUPHe3Vq5e88cYbVulLNQ4xwqKau379OkJDQ8stiHV2dr7r53IVPc/JyUFgYCA+/fRTDB8+3IbvSFsiggEDBsDFxQXbLH0F4YaYmBgMGzYMaWlpaNmypVX6VAUDi8zy8/PvuCyjskdxcTFef/11LFiwwGb1r18PLFhg2q1z61bT+YuAabudoUNNr2VnA9XJ088++wxTp05FcnKyVcOjR48e+Mtf/oIPPvjAan2qwKF2a6DaqV+/PurXr1/tf5giAoPBYF4Ma0tabgl9/vx5/P3vf8eiRYusPtKZPn06goODMWXKFNxrgVvNVMURFjmMivbcAoDoaKBtW9Ni1pAQ0wgrKQlwdweaNDGdnHwruXEBwcPDA5s3b7bm2zDr1q0b+vXrhyhLHs+tGAYWOYyKTkgGKp4SenmZriwCptHYgAHHcPr082jcuDEaN26MoqIiJCYmIjk5Ga1vHKio5ZkBVbF582a8+OKLOHv2rNXugrB3nBKSw6nKltCZmeUfubmN8Mcf78BgMMBgMCAhIQFubm645557AABz5szBDz/8gL1791rhHZgMHToUPj4+WLx4MWbNmmW1fu0ZR1hEFSgpKUH79u0xevRoTJkyBRkZGfDx8cG2bdvQ18JH2ezevRuPPfYY6tatiw0bNuCVV17Bl19+idatW5fbQ6vKCgpMN126uJiGmBERpvuZFMTAIrqDlStXYtq0aTh79iwaNWqEsLAw/PbbbxYdZe3evRuDBg1CYmIi/P39kZSUhIEDByInJwd5eXnmr3NxcYFOp8OQ7t2x/OrV8qd4lD38/Ew3WC5ZYroaMWiQaTg5cSJgoX3dLI2BRXQHRUVFePDBBzF+/HhMmjQJFy5cgI+PD3744Qf07t1b8/70ej38/PwwZswYvPvuuygsLET37t3RtWtXrFixAoWFhbctJ/HKz8cjv/9e8ab4f/kLMHs2EBYGzJgBNG9u6uippwBVDzix+lJVIoV8+umn0rx5c8nLyxMRkTFjxki/fv0s0tfIkSOlS5cuUlRUJCIiERER0rp1azEYDLVr+KOPRLZtMz2/elXkhRdqWantMLCI7qKwsFDatGkjixcvFhGRc+fOiaurqxw4cEDTfjZt2iSurq5y9OhRERFJSEgQFxcX2bVrV+0bz8sTGTtWZMIEkeHDRVJTa9+mjXBKSFSJpUuXYt68eeZdLV5++WVcunQJ27dv16T9rKws+Pn5Ydy4cYiIiEBhYSG6deuGHj161HjfNUfFwCKqhNFohLe3t3lXi7S0NDz00EP48ccf0b1791q3P2LECPz666+Ii4uDs7MzZsyYgS+++ALHjx+/435q/7VsO8AjUsPChQvlvvvuE6PRKCIiw4cPl4CAgFq3u3HjRnF1dZVjx46JyH+mgrt37651246IgUVUBfn5+dKyZUvzFjO//fabODk5SUJCQo3bvHz5sjRt2lRm3jhWKD8/Xx5++GEZN26cJjXf0ZYtIi+9ZNk+LIRTQqIq+uCDD7B06VKcOnUKrq6uCA4OhtForPFmhSEhITh16pR5Kjh9+nSsX78ex44ds+z5hGlpwEMPAT/+CGgwpbUqWycmkSpyc3Pl3nvvlVWrVomISEpKijg5OZmv7FXHhg0byk0F4+PjrTsVfPFFEQ2mtNbGwCKqhjlz5oi3t7d5rdTMmTMlKSmpWm1cvnxZ7rnnnnJTwfbt28urr76qeb13dOqUiLOzSHy89frUAKeERNWQm5uLdu3aYeHChTXeWfXatWuYN28eZsyYAVdXV4SHh+Orr76y/FTwVs8+C6lTB3W+/tp6fdYSA4uommbNmoW1a9ciJSXFfJBqTcXHx6NXr17YsWMHHnvsMY0qrJrc5GT0HzQIK2Ji4Ovra9W+a4qBRVRNer0eTz/9NPbu3Yt69eqVO46+qo8WLVrAaDSic+fO6Nu3Lz7++GObvJfnnnsOImKTszFrgoFFVANZWVk4ceJEuROds7Kyyj2/9bXi4mLz93t4eKBhw4bw9PREXFyczRaIpqSkoGPHjvjll1/g7+9vkxqqg4FFZCU5OTm3BdqwYcPg5ORk07qeeuopuLm5Yd26dTatoyoYWET/5RISEtCrVy+kp6ejWbNmti7nrhhYRIQLFy7gvvvus3UZlWJgEZEyandNlojIihhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESmDgUVEymBgEZEyGFhEpAwGFhEpg4FFRMpgYBGRMhhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESmDgUVEymBgEZEyGFhEpAwGFhEpg4FFRMpgYBGRMhhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESmDgUVEymBgEZEyGFhEpAwGFhEpg4FFRMpgYBGRMhhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESmDgUVEymBgEZEyGFhEpAwGFhEpg4FFRMpgYBGRMhhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESmDgUVEymBgEZEyGFhEpAwGFhEpg4FFRMpgYBGRMhhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESmDgUVEymBgEZEyGFhEpAwGFhEpg4FFRMpgYBGRMhhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESmDgUVEymBgEZEyGFhEpAwGFhEpg4FFRMpgYBGRMhhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESmDgUVEymBgEZEyGFhEpAwGFhEpg4FFRMpgYBGRMhhYRKQMBhYRKYOBRUTKYGARkTIYWESkDAYWESnj/wFM0nzB7I7j5wAAAABJRU5ErkJggg==\" alt=\"Mol\"/></td>\n",
" <td> CHEMBL884722</td>\n",
" </tr>\n",
" <tr>\n",
" <th>72</th>\n",
" <td> CHEMBL1672305</td>\n",
" <td> 8c, MCL-527</td>\n",
" <td> CCN1CCc2cc(OCCCF)cc3c2[C@H]1Cc4ccc(O)c(O)c34</td>\n",
" <td> <img src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
" <td> CHEMBL1680102</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 65,
"text": [
" parent_cmpd_chemblid name_in_reference SMILES ROMol assay_chemblid\n",
"11 CHEMBL97333 15d CN1CCC(CCN2CCC(CC2)c3cn(c4ccc(F)cc4)c5ccc(cc35)c6ncn(C)n6)C1=O <img src=\"data:image/png;base64,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\" alt=\"Mol\"/> CHEMBL674985\n",
"17 CHEMBL344270 3c Clc1ccc(cc1Cl)N2CCN(Cc3c[nH]c4ccc(cc34)C#N)CC2 <img src=\"data:image/png;base64,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\" alt=\"Mol\"/> CHEMBL675671\n",
"21 CHEMBL147829 3 OC1(Cc2ccc(Cl)cc2)CCN(CCCC(=O)c3ccc(F)cc3)CC1 <img src=\"data:image/png;base64,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\" alt=\"Mol\"/> CHEMBL671515\n",
"43 CHEMBL196598 6f COc1ccc(NC(=O)N2CCN(CC2)c3ccc(cc3)C(F)(F)F)cc1N4CCN(C)CC4 <img src=\"data:image/png;base64,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\" alt=\"Mol\"/> CHEMBL884722\n",
"72 CHEMBL1672305 8c, MCL-527 CCN1CCc2cc(OCCCF)cc3c2[C@H]1Cc4ccc(O)c(O)c34 <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAASwAAAEsCAYAAAB5fY51AAAm/ElEQVR4nO3deVRV170H8C8ziAqKKGrFOhtwRuOEiIoKwgXF4UUjNTFVE2ON8fWpazUJpl1NSF9fo6laNamJ2qcJxIFBFGcELyqIMbEStRpHiBoGGWS+v/cHT5obQBHvvecc8v2s1VXuOdyzf2et+GWfc/bZ20pEBEREGmCtdAFERI3FwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJrBwCIizWBgEZFmMLCISDMYWESkGQwsItIMBhYRaQYDi4g0g4FFRJphq3QBZKy6uhonT55EbGwsRAQhISEYP3680mURqQJ7WCrw8OFD7N27Fy+//DI8PDwQGBiIq1evorCwEMHBwdizZ4/SJRKpAntYCrl9+zZ27dqFmJgYnDp1Ch07dkR4eDj27NmDkSNHwsbGBgAwfvx4vPDCC/jggw+wbNkyZYsmUhgDy0JEBJmZmYiPj0dMTAwuXrwIHx8fhISEYNOmTfD29q73e3PmzIGLiwtmzpyJ77//HlFRURaunEg9rERElC6iuaqsrERycjLi4+MRFxeHO3fuYOzYsQgJCUFYWBh++ctfNvpYKSkp0Ol0mDt3Lj766CNYW/Nqnn5+GFgmVlRUhD179iAhIQFHjhxBZWUlAgMDERISguDgYLi5uTX52BcuXMDkyZMxbtw4fPrpp7CzszNh5UTqx8AygZycHERHRyMhIQGpqalwdXVFaGgoQkJCEBAQACcnJ5O19d1332HixIl47rnnEB0dbdJjE6kdA+sZbd68Gb/5zW/g7u6O0NBQTJ06Ff7+/rC3tzdbmzk5OQgMDISrqyvi4uLg4uJitraI1ISB9QwqKirg4uKCtWvXYsGCBbCysrJY2/n5+QgJCUFZWRn279+P9u3bW6xtIqUwsJ7BmTNnMGbMGBQUFChyaVZSUoLp06fjypUrOHjwIHr06GGRdouLi3HgwAF88803GD58OKZMmWKRdon4qOkZ6PV6DBgwQLH7SM7OzoiLi8PQoUMxZswYfPPNN2Zr6/vvv8fmzZsRHBwMd3d3/OY3v8FXX32F8PBwfPjhh2Zrl+jHGFjPIC0tDaNGjVK0Bnt7e+zYsQM6nQ5jx45FWlqaSY4rIkhNTcWqVavg7e2NTp06Ydu2bfDz80NGRgZycnIQGxuLpKQkrF69GkuXLoXBYDBJ20QNEmqyLl26yM6dO5UuQ0REDAaDREZGirOzsyQlJTXpGOXl5RIXFycLFy4UT09Psbe3l5CQENm0aZPcuHGjwe9lZGRI+/btZe7cuVJRUdHUUyB6IgZWE928eVMAPPYfshLWrl0rjo6OEh0d3ajff/DggWzdulVmzpwpbdq0kdatW0tERIRER0dLXl5eo9v99ttvxdPTU0JCQuThw4dNLZ/osRhYTfT555/LL37xC6XLqNe2bdvEwcFBNm/eXO/+27dvy5o1ayQgIEAcHBykU6dOsnTpUjl06JCUlpY+8fgXL16UjRs31tmenZ0t/fv3Fz8/PykoKHjm8yD6KQZWE73xxhsyc+ZMpctoUGxsrDg5OUlUVJSI1Fy2RUZGio+Pj1hbW4uXl5dERkZKRkaGVFdXP/ZY1dXVcvLkSVmxYoX07t1brK2tZdSoUVJUVFTnd3Nzc2XEiBHSr18/uXPnjlnOjX6+OKyhiebN24VRo5ywaJF6H+nv378f06dPh6enJy5duoTBgwcjNDQUYWFhGDx48GO/W1hYiL179yIhIQGHDx9GdXU1wsLCoNPpEBAQgDZt2jT43ZKSEoSHh9cOt+jZs6epT+3JysqA5csBOzugoACIjAS6d7d8HWRSDKwmePgQcHUFUlKA4cOVrubxdDodDAYDNmzYgK5duz72d7OzsxETE1P7ilHbtm0xY8YM6HQ6+Pr6wtHRsdHtVlRU4MUXX0RqaioOHDiAgQMHPuupPJ2//hXo2RMICgJyc4Fly4Dt2y1bA5kchzU0wdmzgK0tMGSI0pU8WWZmJiIiIhoMq4sXL2L16tUYOnQounTpgs2bN2P06NFITU3FrVu3sHbtWgQEBDxVWAE1wy0+//xz6HQ6+Pv7IzU11RSn03hZWcCjXqSbG1BSYtn2ySw4H1YT6PWAj0/N1Yaa3bx5E9nZ2UZjxQwGA/R6fW1P6vr16xg5ciQiIiIQHR2N7ia8bLKxscGmTZvQpk0bTJ48GTExMeYbFW8wAGlpQE4OMGMG0LcvcO7cv3tYLVqYp12yLGVvoWlTWJjIf/2X0lU82c6dO+s8yTxw4IDY2NjIuHHjZM2aNfLdd99ZpJaoqCixtbWVLVu2mO6gDx+KxMWJvPKKSPv2Ig4OIvPm/XvfwoUiS5eKzJ0rcuWK6dolxagqsFJTU6WyslLpMh7LYBBp105k926lK3mypUuXyqxZs4y2VVRUyA8//KBIPZ999pnY2dnJ//zP/zT9ILduiaxZIzJ6tIitrYiHR00oHTok8qQhGUVFIiUlTW+bFKeawCorK5NevXqpfuDhlSsigMjdu0pX8mRDhw6VDz/8UOkyjOzdu1ccHR1l5cqVjf7O1atXZf2aNWLw9xexsanpTS1YILJvn0hZWeMbf+01kZEjRXJzm1A5qYFqAktE5O7duzJ48GAZNmyY3L9/X+ly6rV1q0iPHkpX8WRFRUVia2srp0+fVrqUOo4ePSqtWrWSxYsX1zsGzGAwSHp6urz11lvSv39/ASDdu3eX/HfeETlxQqSqqmkNFxeLTJwo0r27yL/+9YxnQUpQVWCJ1PxDCwgIkOeee05u3bqldDl1vPpqzS0RtTt+/Li0aNFCte/2paenS7t27WT27NlSUVEhhYWFEh0dLREREeLm5iZ2dnYSEBAga9askWvXrpmu4bIykRkzRDp2FPnqK9MdlyxCleOwysvLMWfOHJw9exYHDx5E7969lS6p1rVrQGUl0KeP0pU83vvvv48DBw4gOTlZ6VIa9NVXXyEwMBA9e/bEhQsXUFpaCn9/f4SFhSE0NBS/+MUvzNNwdTXw6qvArl1AfDwwerR52iHTUzoxG1JVVSXz58+XDh06SGZmptLlaI5Op5NVq1YpXcYTffTRR9KpUyfZuXOnZd8/NBhqHvW2aFFzL4w0QbUDR21sbPDJJ59g7ty5GDduHFJSUpQuSTNEBHq9HiNHjlS6FCNxcXFYvny50barV6/C19cXL7zwgmXnpreyAv70J+Cdd4CwMGDLFsu1DaCqqgpHjhzB8ePHUVZWZtG2tUzVA0etrKzw5z//Ge7u7pg0aRJ27NiBadOmKV2W6l2+fBl5eXmKTy74U4mJiXj48KHRNr1ejzlz5ihUEYCVKwFHRyRt2oSbVVVYsHCh2Zp6NLV0bGws9u3bh8rKSnTv3h1ubm7Yu3cvWrdubba2mw2lu3iNtWHDBrG3tzftwMNG2rlTZNiwmp/j42s+q9mWLVukd+/eSpdRx4ABA2TDhg21n0tKSsTOzk4VTzL/sX272NnZyfvvv2/S4166dEmioqJk9OjRYmNjI7169ZKVK1dKSkqKVFVVSX5+vvj6+oqXl5fcvn3bpG03R6ruYf3Ya6+9BldXV7z00kvIz8+vc2lhbj17Anv2qP91HEAdUzf/1IMHD3DhwgWjutLT02FnZ/fEmSMs4cW5c9Gpc2dMnToVN2/exLp165q0uraI4OTJk0hISEB8fDyysrIwatQo6HQ6bNq0Cd7e3ka/7+rqiqSkJMycORO+vr44ePAgevXqZarTan6UTsyndfjwYWnZsuVTDTxsitJSkcREkcrKmh5VbKzI7Nk1b4KovYfl7e0tmzZtUroMI0lJSdK6dWup+tEYqvfee0/GjBmjYFV1paeni7u7e+1wi8Z43NTS169fb9QxKisr5aWXXhIPDw/5isMtGqS5wBIROX36tLi5uTU48LCpcnNFtm+vGabTsqVImzYi//xnTUDFx4vs2iUyZ466Ays3N1esrKzkm2++UboUI6tXr5aAgACjbTqdzux/eJoiKytLPD09JTg4WEoaeJXHVFNL/5jBYJA333xTXF1dJTU19VlOodnSZGCJiFy4cEE6d+4sc+bMeabBkRkZIpGRIj4+ItbWIl5eNZ8zMkQeZeGjwDIYau5lPQqsBw+e+TRMLjExUVxcXEwa5KYwefJkeeedd2o/GwwGcXNzk7179ypYVcOys7NlwIABMnz48Np3L388tbSjo+NTTy3dWFFRUdKiRQtJTEw02TGbC80GlojItWvXpGfPno/9S1ifs2fPyp//fE8GDap5L3DQoJqQeprhXqdOibi7i6jgfrGRt99+WyZPnqx0GUaqqqqkdevWsn///tpt3377rVhZWan2FSyRmlfFhgwZIv3795dx48aJra2tdO3aVZYuXSqHDx8264v669atE0dHR9WsyqQWmg4sEZGcnBwZOHCg0V/Cn6qoqJBDhw7JkiVLxNPTU2xtbeXXv06QtWtFGnmLoV5RUSKOjuqauWHChAmyevVqpcsw8vXXX4u1tbXk5+fXbtuyZYv06tVLuaIa6cGDB7J582aJjIy0+ADm//3f/xV7e3vFXmBPys2VJZcvyx9v3JDTKrmc0HxgiYjk5+fL6NGjxdvbu3bhg5ycHNm0aZOEhISIk5OTdOjQQRYuXChxcXEmnQ1iwwYRe3sRBUZb1FFZWSnOzs5y8OBBpUsxsmnTJvH29jbatmDBApn3aO4qalBCQoI4OTkpcq8vKTdXjv3oj4waNIvAEqn5Szhu3Djp0aOHTJo0SRwcHKRjx46ycOFCSUxMlLKnmYbkKe3YURNaf/mL2ZpolMzMTLGxsZHCwkJlC/mJl156SRYsWGC0zdvbu96lwqiu5ORkcXFxkSVLlpj93uSdsjJJ/v9XpH7cw7plxn8/T0Mz47CepHXr1khMTMTnn3+OS5cu4fe//z2GDRvWpLE0T2v2bKB1a2DWLODuXSAqyuxN1kuv16Nfv35o1aqVMgU0QK/XY9WqVbWf8/PzcfHiRdWNFVMrPz8/pKamYvLkycjPz8enn34KOxMOCLxcWorjBQU4np+Py6Wl6NOiBcb8/2tS093d4e/qarK2nlWzCSwAcHR0xEsvvaRI28HBwNGjNf9fXAx89BFggaysVVJSgn379mHo0KGWa7QR7t+/jytXrhi913j69Gm0bt26ziBKali/fv2QmpqKiRMnIjw8HNHR0XBycmrSsSpFkFZYiMP5+Uh78ABF1dUY0qoVdO3aYayrKzrZ25u4etNpVoGltOHDgf37gWnTBM7OW/HeexGwsbExW3v37t1DXFwcYmNjceTIEbRt2xZff/01Ll26hD4qmf/m1KlTcHNzM6onLS0NI0aMsEjvtznp1q0bUlJSEBgYiMDAQMTFxTX6hfGysjKkXbiAk+7uOFFQgOLqagxt3RqvdeqEMa6ucK+nxzapbVtTn8Iz438xJjZsGHD48HXs2PE2XnjhBZSXl5vs2CKC1NRUrFq1Ct7e3vDw8MDGjRvh4+OD9PR03Lx5EzqdDiNHjsTJkydN1u6zeBROVlZWtdvUOJOEVnTs2BHHjx9HVVUVxo8fj3v37jX4u7m5udi2bRumT5+Odu3a4Vf/8R+orK7GSk9PHB40CB/17Ilwd/d6w0q1lL6J1lzl5OTIgAEDxM/P75nmeaqoqKh97aNr165iZ2f3xNc+oqKixNnZWRUDD8eOHSt//OMfaz9XVVVJq1atVPckU2uKi4tl8uTJ0r17d/nXj6Z7zsjIkMjISPHy8hIA4uPjI5GRkZKRkaG6wcRNwcAyo7y8PBk1apT069evdrhFY/z4tY+2bdtKq1atal/7yG3kAgp//etfxcHBQdGBh+Xl5eLk5CRHjx6t3Xbu3DlVPsnUoocPH4pOpxNPT09ZsmSJ9OvXT6ysrMTHx0d+//vfN8t3EhlYZlZcXCyBgYF1/hL+1J07d4xe++jYseNTvfZRWFgoBoPBaNv27dvF3t5e/qLQeIv09HSxtbWV4uLi2m3r16+XgQMHKlJPc1RZWSkffPCBhIaGyvr161W5DoIpMbAsoLy8XGbNmiUdO3aUr7/+unb7P//5T4mMjBQfHx+xtraW5557rsnd9wkTJsiiRYvqfC8uLk6xgYdbt26VIUOGGG2bO3euvPbaaxavhZoHBpaFVFZWSkREhLRv316WLFkiQ4YMEQAyYMAAefvttyUjI6NOD+lpXLhwQTp16iQ6na7OSP7jx4+Li4uLyWe3aIyfvpjevXt32bZtm0VroOZDlavmNFcigvfeew/nzp2Dr68vwsLC0K1bN5Md/7vvvsOkSZPQuXNnxMXFGU25m5mZiaCgIEyYMAFbt2416cDDxsrJyUGnTp1w5coV9OzZ0+Ltk/ZxWIMFWVlZwd3dHV9++SWWLVtm0rAC/j1Op6CgAOPHj8f9+/dr9w0ZMgQnTpzAyZMnERQUhOLiYpO23RhffvklPDw8GFbUZAwsC9u9e7dZj+/h4YHjx4/D0dERfn5+uHXrVu2+Pn364NSpU7h37x4mTJiA3Nxcs9ZiMBhw8uRJrFixAr1798bSpUvxhz/8waxtUvPGwLKgU6dO4YcffjB7O66urjh48CC6desGX19fXLp0qXbfo4GH1tbW8PPzw+3bt03a9oMHD7Bt2zbMmjULbm5uGD9+PLKysvDb3/4WN27cwK9//WuTtkc/L7yHZUELFy7EzZs3ceDAAYu0V1FRgXnz5uHo0aM4cOCA0WIPJSUlCA8Px+XLl5954YM7d+7gyy+/RExMDE6fPg1nZ2eEhoZCp9MhICAAbdq0McXpEHGku6UUFRVJy5YtZc6cORZt12AwyLJly6Rly5Zy6NAho33l5eUyY8aMJq2u/dMR1Z07d5alS5dKSkqKWWfipJ83BpaFfPrppwJAli5dqkj7UVFR4uDgILt27TLaXlVVJQsWLBAXFxc5ceJEg9+vrKyUQ4cOydKlS6Vbt25Gr31cuHDB3OUTiQgDy2LGjBkjAOTdd99VrIZ169aJnZ1dncVoDQaDrFixok6gFRUVSXR0tERERIibm5vY2tpKQECArFmzRq5du2bp8omazwR+avbtt98iJSUFAODm5qZYHa+//jpcXV0xf/58FBQU4M033wRQM9zigw8+gKOjI2bPno3ly5fj5s2bSExMRElJCcaOHYvVq1cjLCwMXbp0Uax+IgaWBXz22We1P7dr1065QgC8+OKLcHV1xcyZM3H37l1E/Wh61HfffRcFBQXYvXs3Bg0ahPXr12PKlClwVdGMk/TzxsAys8rKSlUFFgAEBwcjLi4O06ZNQ6tWrfC73/2udp+joyP69u2LL774QsEKierHwDKzAwcO4O7du7Wflbwk/LGAgAAcOXIEtrbG/wno9XoEBwcrVBXR43HgqJn9/e9/N/qshh7WI88//zyGDBlS+7miogIZGRlcHIJUiwNHzSgnJweenp6oqqqq3VZaWgpHR0cFq2rY6dOn4efnh4KCgiYvcEBkTuxhmdH27duNwsrZ2Vm1YQXUXA4OGjSIYUWqxcAyExGpczmolvtXDUlLS+PlIKkaA8tM9Ho9Ll++bLRNTfev6nPy5EmuZkOqxsAyky1bttTZpubAunHjBrKzs+Hr66t0KUQNYmCZQVFRUb3jmNR8SajX69GlSxd06tRJ6VKIGsTAMoPo6GiUlJTU2a7mHhbvX5EWMLDMoL7LQUD9PSzevyK1Y2CZ2MWLF6HX6+vdp9bAKi4uxvnz59nDItVjYJnYsWPH6rzu8ohaLwkzMjJgb2+PQYMGKV0K0WMxsEzs9ddfR2lpKS5cuICVK1eiT58+8PLyAqDewNLr9Rg2bJgiS38RPQ0GlhnY2trC29sbixYtQnV1NTp27Ijz589j2LBhSpdWL95wJ61gYJnRo3UCf/jhByxYsMDoNR21EBGkpaXxhjtpAgPLzB6tE2hnZwc/Pz/cuXNH6ZKMXLp0CXl5eexhkSYwsCzg0TqBXbt2ha+vL65cuaJ0SbX0ej169eql2ieYRD/GwLKQFi1aYO/evRgxYgTGjBmDr776SumSAPD+FWkLA8uC7O3tsWPHDsyePRvjxo2rXZhCSRwwSlrCKZItzMrKCh9++CE8PDwwceJE7NixA+Hh4YrUkpeXh6ysLPawSDMYWApZuXIlnJ2d8cILL2Djxo2YP3++xWs4ffo0XF1d4e3tbfG2iZqCgaWgJUuWwNXVFa+88gry8vLw29/+1uxtGgwGnD59GrGxsfjiiy/wy1/+Evn5+Wjbtq3Z2yZ6VryHpbC5c+di165deOedd7Bq1SqYY4r9srIyJCYmYtGiRejcuTN8fX2RnJyMiIgIGAwGjB07FtnZ2SZvl8jUuAiFSiQnJyMsLAzTpk3Dxx9/3OD7iI2VnZ2NmJgYJCQkIDU1Ffb29ggLC4NOp0NAQADatGkDACgpKcGMGTNw/vx5JCUloX///qY4HSKzYGCpSGZmJoKCgjBq1Cjs3LnzqResuHjxIqKjo5GQkIBz587Bw8MDM2bMgE6ng6+vb4PHq6iowLx583Dw4EEkJCTwqSGpFgNLZa5du4aJEyeia9euiI2NRatWrRr83aqqKhw/fhzx8fFISEjAtWvX4OXlhZkzZ0Kn02Hw4MGwtm7cVb+IYPny5fj444+xe/duTJo0yVSnRGQ6QqqTnZ0t/fv3l6FDh8q9e/eM9hUXF0t0dLRERERIu3btxNraWkaPHi1r1qyRq1evNrqNkydPyvbt2+tsj4qKEgcHB4mJiXnm8yAyNQaWSuXm5srIkSPlueeek8zMTNm0aZOEhISIk5OTODs7y8yZM2Xr1q1y//79Jh0/OjpaHBwc5MMPP6yzb926dWJnZyebN29+xrMgMi1eEqpYQUEBJk6ciLt37yI/Px+BgYEIDQ1FcHCwSYYhJCcnIzQ0FPPmzcOaNWuMLh937NiBl19+GX/4wx+wYsWKZ27rqZWVAcuXA3Z2QEEBEBkJnDkDODoCU6cCCQk12+fOtXxtpBiOw1IxV1dXTJ48GSdOnMDly5dNvmr02LFjcfToUQQFBSE/Px+ffvpp7dPJOXPmwMXFBbNmzUJeXh7ef/99WFlZmbT9x/r4Y0CnA4KCgNxcYNkyIDjYcu2TKnEclsqdOXMG48ePN9sS9z4+Pjhx4gSSk5MRHh6O0tLS2n3BwcE4evQoPvnkE7z88suWnc8rKwsYPLjmZzc34NEqRBs3Aq++CmzYYLlaSDUYWCpWXV2NU6dOGb3rV1lZafLBpX379kVqaiouX76MoKAgPHjwoHbf8OHDkZycjMOHD2PGjBkoKyszadu1cnOBbduARYseFQWcO/fvfS1a1Pz86qs1obV4sXnqIFVjYKnYhQsX8PDhQ4wYMaJ227Zt28wyTsrT0xMnTpxAYWEhxo8fj3v37tXu8/b2RmpqKi5evIgpU6agqKjINI1+9x2wZg0wfjzg4VFzn8rREXj4EFiwANi7F3jjjZrLwdWrTdMmaRpvuqvY3/72N2zcuBHnz5+v3TZ//nxYW1vjk08+MUubxcXFmDZtGq5du4aDBw+iR48etfvu3r2LwMBA2NnZITEx8ekX1aiqAo4fB+Lja/536xbg7w+EhNTcr+re3aTnQs0Pe1gqVt/keuaev6ply5ZISEjAwIEDMWbMGHzzzTe1+zp06IBjx47BwcEBfn5+uH379hOPV1FRgUOHDmHJkiUo9vcHpkwBLl6seQJ49Spw6FBNL4phRY3AwFKxn4bTDz/8gMuXL5t9/ioHBwfExMQgMDAQY8eORVpaWu0+V1dXHD58GH379oWvry8uX75c5/uFhYX44osvMHv2bLRv3x7Tp0/H/fv3kb18OXDvXk1ILVkCeHqa9TyoGVJ0FBg1KCcnRwDIlStXarfFx8dL27ZtxWAwWKQGg8Egb775pjg7O8uBAweM9lVVVcn8+fOlQ4cOkpmZKVlZWRIZGSk+Pj5ibW0tffr0kZUrV0pKSopUVVVZpF5q/jgOS6XS0tLg4eGBnj17Gm0bMWKExcZDWVlZ4S9/+Qs6dOiA0NBQbN++HbNmzQIA2NjYYPPmzXjttdcQHh6OGzduwMvLC2FhYdiwYQOGDRtm2XFb9LPAwFKptLQ0DB8+3GibXq/HhAkTLF7LypUr0bJlS8ydOxf5+flY9P9DD2xsbLB48WJs2bIFmZmZXOqezI73sFTqp/evqqqqkJ6ertj866+//jrWr1+P6OhoGAyG2u1paWnw8vJiWJFFcFiDCpWXl8PFxQWHDh3CmDFjAABnz57FiBEjUFBQAGdnZ8VqMxgMRu8c/upXv0KLFi2wceNGxWqinw/2sFQoMzMTIoKhQ4fWbtPr9ejfv7+iYQWgzvxaXCaMLImBpUJ6vR6DBw+Gk5NT7TY1Lnj6/fff4+rVq6qri5ovBpYK1RdOaWlpquvJnDp1Cu3btzd6kklkTgwsFUpNTTUKpzt37uD69euq68k8ClEOXyBLYWCpzPXr13H37l2MHj26dltaWho6duyIbt26KVhZXbx/RZbGwFIZvV6Prl27olOnTrXb1Hg5WFFRgYyMDNX1+qh5Y2CpjFbuX2VmZsJgMBg9ySQyNwaWyvz0MqusrAyZmZmq68nU9ySTyNwYWCpSXFyM8+fPG4XT2bNnAdRMZawmahxmQc0fA0tFzpw5AycnJwwcOLB2W2VlJSIiIuDg4KBgZXXxhjspgS8/q0hWVhZ69uxZu3INAPj7+8Pf31+5oupx/fp1ZGdnGz3JJLIE9rBUZNKkScjKysJbb72ldCmPpdfr4enpafQkk8gSGFgq0qtXLyQnJ2Pjxo2IiIhAZWWl0iXVi/evSCkMLJV5tKzWsWPHMH36dKN1AtWC969IKQwsFfL29kZKSgqysrIQFBSEwsJCpUuqVd+TTCJLYWCpVLdu3ZCSkoIHDx7UWSfQUqqrq3H//n2jbY+eZHLCPlICA0vFPDw8cOzYMTg5OcHPzw83b940e5ulpaWIi4vDK6+8go4dO+KVV14x2q/X6zF06FCjJ5lElsLAUjlXV1ckJSWhR48eGDFihNE6gaZy584drF27Fr6+vmjVqhUWL16Mli1bYvfu3di9e7fR7/KGOymJUyRrRFVVFRYuXIjY2Fjs27fPaPn6pjh79izi4+MRExODixcvwsfHByEhIZg5cya8vb3r/Y7BYEC7du2wbds2hISEPFP7RE3Bfr1G2Nra4u9//zvatm2LgIAA7N69G5MmTWr096uqqnD8+HHEx8cjPj4et27dgr+/PxYuXIjQ0NAnTl1TWlqKrVu3oqCgAMOGDXvW0yFqEvawNOiDDz5AZGQk/vGPf2DGjBkN/l5xcTH279+P+Ph4JCYmoqysDFOmTEFISAimTJmCdu3aPbad3Nxc7Nu3D7GxsUhKSoKDgwNatGgBPz8/fPbZZ7CzszP1qRE9noKLuNIz2LBhg9jZ2cnmzZvr3f/f//3f0qZNG2nZsqXMmDFDtm/fLnl5eU88bkZGhkRGRoqXl5cAEB8fH4mMjJSMjAyprq6WO3fuSL9+/cTf318ePHhg6tMieiz2sDRsz549mDNnDt59912sWLHCaN+JEydQVFSECRMmwNHRscFjNHSpGBISAp1Oh+7du9f5Tl5eHoKDg1FVVYXExES4u7ub/NyI6sPA0rijR49i6tSpWLx4Md5///1Gza/+00vF8vJyBAUFNfpS8dExwsPDcevWLRw8eBBdunQxxekQPRYDqxlIT0/HlClTEBwcjE8++aTeMVJ3795FbGws4uPjceTIEbRu3RphYWEICQlBQEBAkybiKy8vx4svvoiMjAwkJSWhT58+pjgdogYxsJqJrKwsTJo0CT4+Pvj888/h6OiIS5cuYe/evYiPj8epU6fQo0cPTJs2DSEhIRg5ciRsbGyeud3q6mosWrQI8fHx2L9/P4YMGWKCsyGqHwOrGbly5QomT56MLl26oLy8HOnp6ejTpw/CwsIQFhaG559/vs7KzaZgMBiwZMkSzP7uO4yJjASecYwYUUMYWM1MdnY29uzZg5KSEkydOhW9e/e2XONvvQWsWQPs3g08xRgxosZiYJFpbdwIvPEG8Le/AfPnK10NNTMc6U6m9eqrQIcOwJw5QH4+8J//qXRF1Iywh0XmcfQoMHUqsHgxEBWldDXUTDCwyHzOnAGmTAFmzQLWrQPMcMOffl54SUjm8/zzQFISEBQEtGwJ/OlPSldEGsceFpnft98C1dVAA9PWEDUWA4ssp6wMWL4csLMDCgqAyMiay0ZHx5r7XQkJNdvnzlW4UFIrXhKS5Xz8MaDT1Vwi5uYCy5YBwcFKV0UawrugZDlZWcDgwTU/u7kBJSU1P2/cWDMcYsMG5WojTWBgkeX07QucO1fzc24u0KJFzc+vvloTWosXK1cbaQIvCclyFiyouQw8cADIywNWrwYyMpSuijSEN92JSDN4SUhEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpBgOLiDSDgUVEmsHAIiLNYGARkWYwsIhIMxhYRKQZDCwi0gwGFhFpxv8B5lwSoat0SpAAAAAASUVORK5CYII=\" alt=\"Mol\"/> CHEMBL1680102\n",
"\n",
"[5 rows x 5 columns]"
]
}
],
"prompt_number": 65
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Construct fingerprints:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fps = [Chem.GetMorganFingerprintAsBitVect(m,2,nBits=2048) for m in mols['ROMol']]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 71
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now the distance matrix:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"dist_mat = []\n",
"for i,fp in enumerate(fps):\n",
" dist_mat.append(DataStructs.BulkTanimotoSimilarity(fps[i],fps,returnDistance=1))\n",
"dist_mat=numpy.array(dist_mat)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 74
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And now do the MDS into 2 dimensions:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mds = manifold.MDS(n_components=2, dissimilarity=\"precomputed\", random_state=3, n_jobs = 4, verbose=1,max_iter=1000)\n",
"results = mds.fit(dist_mat)\n",
"coords = results.embedding_\n",
"print 'Final stress:',mds.stress_"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress: 4082.51507338\n",
"breaking at iteration 332 with stress 4176.29585114\n",
"breaking at iteration 311 with stress 4138.43956408\n",
"breaking at iteration 474 with stress 4120.48381345\n",
"breaking at iteration 533 with stress 4082.51507338\n"
]
}
],
"prompt_number": 77
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And plot the points:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"rcParams['figure.figsize'] = 6,6"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 78
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"scatter([x for x,y in coords], [y for x,y in coords],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 79,
"text": [
"<matplotlib.collections.PathCollection at 0x77e4b10>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAFtCAYAAADvWmr3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ncfFnjDEHxMWfMcYcEBd/xhhzQP8HVUK8UqYP8kcAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x7617a90>"
]
}
],
"prompt_number": 79
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nice picture. How accurate is it?\n",
"\n",
"The strain values above lead me to believe that there are probably some real problems here.\n",
"\n",
"The overall strain value isn't particularly easy to interpret, so we'll check up on things by comparing the embedded distances with the Tanimoto distances we're trying to reproduce."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import random\n",
"def distCompare(dmat,coords,nPicks=5000,seed=0xf00d):\n",
" \"\"\" picks a random set of pairs of points to compare distances \"\"\"\n",
" nPts=len(coords)\n",
" random.seed(seed)\n",
" res=[]\n",
" keep=set()\n",
" if nPicks>0:\n",
" while len(res)<nPicks:\n",
" idx1 = random.randint(0,nPts-1)\n",
" idx2 = random.randint(0,nPts-1)\n",
" if idx1==idx2: \n",
" continue\n",
" if idx1>idx2: \n",
" idx1,idx2=idx2,idx1\n",
" if (idx1,idx2) in keep: \n",
" continue\n",
" keep.add((idx1,idx2))\n",
" p1 = coords[idx1]\n",
" p2 = coords[idx2]\n",
" v = p1-p2\n",
" d = sqrt(v.dot(v))\n",
" res.append((dmat[idx1][idx2],d))\n",
" else:\n",
" for idx1 in range(nPts):\n",
" for idx2 in range(idx1+1,nPts):\n",
" p1 = coords[idx1]\n",
" p2 = coords[idx2]\n",
" v = p1-p2\n",
" d = sqrt(v.dot(v))\n",
" res.append((dmat[idx1][idx2],d))\n",
" return res"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 80
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"d = distCompare(dist_mat,coords)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 81
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"scatter([x for x,y in d],[y for x,y in d],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 82,
"text": [
"<matplotlib.collections.PathCollection at 0x78d0c50>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAFtCAYAAAAAmAHJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niHSGg5+ISGf+Afl9O5s/ih+0AAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x75f9e10>"
]
}
],
"prompt_number": 82
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Yikes... that's no good. This really isn't so surprising given how much stress was left.\n",
"\n",
"Let's try increasing the dimensionality to see how much improvement we can get:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mds2 = manifold.MDS(n_components=20, dissimilarity=\"precomputed\", random_state=3, n_jobs = 4, verbose=1,max_iter=1000)\n",
"results = mds2.fit(dist_mat)\n",
"coords = results.embedding_\n",
"print 'Final stress:',mds2.stress_"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress: 83.6518627219\n",
"breaking at iteration 227 with stress 85.4449912882\n",
"breaking at iteration 221 with stress 86.7300769015\n",
"breaking at iteration 232 with stress 83.6518627219\n",
"breaking at iteration 234 with stress 85.9502931801\n"
]
}
],
"prompt_number": 83
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"d = distCompare(dist_mat,coords)\n",
"scatter([x for x,y in d],[y for x,y in d],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 84,
"text": [
"<matplotlib.collections.PathCollection at 0x5b8af90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAFtCAYAAAAAmAHJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x55f93d0>"
]
}
],
"prompt_number": 84
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Not so bad... of course, we can't visualize 20 dimensions.\n",
"\n",
"What about if we try doing dimensionality reduction on the 20D results instead of using the distance matrix?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mds3 = manifold.MDS(n_components=2, random_state=3, n_jobs = 4, verbose=1,max_iter=1000)\n",
"results3 = mds3.fit(coords)\n",
"coords3 = results3.embedding_\n",
"print 'Final stress:',mds3.stress_"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress: 3987.0547543\n",
"breaking at iteration 263 with stress 4075.27258547\n",
"breaking at iteration 299 with stress 4179.52713573\n",
"breaking at iteration 367 with stress 3987.0547543\n",
"breaking at iteration 366 with stress 4031.85189373\n"
]
}
],
"prompt_number": 85
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The strain is still really high. This isn't that surprising given that we already tried the same thing from the distance matrix.\n",
"\n",
"Ok, so MDS doesn't work. Now that we have actual coordinates, we can use some of the other scikit-learn manifold learning approaches for embedding the points.\n",
"\n",
"Instead of jumping all the way to a 2D system, where we're really unlikely to get decent results, start by dropping down to 10D.\n",
"\n",
"First MDS in 10D:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mds3 = manifold.MDS(n_components=10, random_state=3, n_jobs = 4, verbose=1,max_iter=1000)\n",
"results3 = mds3.fit(coords)\n",
"coords3 = results3.embedding_\n",
"print 'Final stress:',results3.stress_\n",
"ds = distCompare(dist_mat,coords3)\n",
"scatter([x for x,y in d],[y for x,y in d],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress: 232.247671016\n",
"breaking at iteration 206 with stress 232.247671016\n",
"breaking at iteration 226 with stress 239.234800226\n",
"breaking at iteration 205 with stress 239.046196976\n",
"breaking at iteration 255 with stress 242.038671318\n"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 86,
"text": [
"<matplotlib.collections.PathCollection at 0x6f83090>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAFtCAYAAAAAmAHJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7806850>"
]
}
],
"prompt_number": 86
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now try locally linear embedding:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"lle = manifold.LocallyLinearEmbedding(n_components=10,random_state=3,max_iter=1000)\n",
"results3=lle.fit(coords)\n",
"coords3=results3.embedding_\n",
"print results3.reconstruction_error_\n",
"d = distCompare(dist_mat,coords3)\n",
"scatter([x for x,y in d],[y for x,y in d],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"-8.47551453712e-15\n"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 87,
"text": [
"<matplotlib.collections.PathCollection at 0x7e22c90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAFtCAYAAAAAmAHJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x59b4050>"
]
}
],
"prompt_number": 87
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ick! What about Isomap?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"embed = manifold.Isomap(n_components=10,max_iter=1000)\n",
"results3=embed.fit(coords)\n",
"coords3=results3.embedding_\n",
"d = distCompare(dist_mat,coords3)\n",
"scatter([x for x,y in d],[y for x,y in d],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 88,
"text": [
"<matplotlib.collections.PathCollection at 0x7ef3350>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAW8AAAFpCAYAAABTZakJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7e42050>"
]
}
],
"prompt_number": 88
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Also pretty grim. Does spectral embedding work?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"embed = manifold.SpectralEmbedding(n_components=10)\n",
"results3=embed.fit(coords)\n",
"coords3=results3.embedding_\n",
"d = distCompare(dist_mat,coords3)\n",
"scatter([x for x,y in d],[y for x,y in d],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 89,
"text": [
"<matplotlib.collections.PathCollection at 0x68dca90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAFtCAYAAAAAmAHJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsnXd4FNXXx8+mQhJ6J4QeICGQANJbEFGK9CKKiqGIgBQb\ndgVFBCkCooiiWBCVH4iiBBCRAFKlKCgdKQklSCcBUu/7x/cdZ+7MbEl2w252z+d55mFn5s6du7Pk\n3DunWoQQghiGYRifwc/dA2AYhmHuLCz4GYZhfAwW/AzDMD4GC36GYRgfgwU/wzCMj8GCn2EYxsdw\nSvAnJydThw4dqH79+hQTE0Nz5841tElKSqISJUpQo0aNqFGjRjR58mRnbskwDMM4SYAzFwcGBtK7\n775LcXFxlJaWRk2aNKFOnTpRVFSU1K59+/a0cuVKpwbKMAzDuAanVvwVK1akuLg4IiIKCwujqKgo\nOnv2rKEdx4gxDMN4Dk6t+LWcPHmS9u7dS82bN5eOWywW2rp1K8XGxlJ4eDjNmDGDoqOjDW0YhmGY\nvJHvRbVwATdu3BBNmjQRK1asMJy7fv26SE9PF0IIkZiYKCIjIw1tXDQMt/D666+7ewhOweN3Lzx+\n91KYx++M3HTaqycrK4v69u1LDz/8MPXq1ctwvlixYhQSEkJERF26dKGsrCy6fPmys7dlGIZh8olT\ngl8IQUOHDqXo6GgaP368aZvU1NT/Xkd27txJQggqXbq0M7dlGIZhnMApHf+WLVto8eLF1LBhQ2rU\nqBEREU2ZMoVOnz5NREQjRoygZcuW0fz58ykgIIBCQkLom2++cX7UHkR8fLy7h+AUPH73wuN3L4V9\n/PnFIoT7XW4sFgt7/jAMw+QBZ+QmR+4yDMP4GCz4GYZhfAwW/AzDMD4GC36GYRgfgwU/wzCMj8GC\nn2EYxsdgwc8wDONjsOBnGIbxMVjwMwzD+Bgs+BmGYXwMFvwMwzA+Bgt+hmEYH4MFP8MwjI/Bgp9h\nGMbHYMHPMAzjY7DgZxiG8TFY8DMMw/gYLPgZhmF8DBb8DMMwPgYLfoZhGB+DBT/DMIyPwYKfYRjG\nx2DBzzAM42Ow4GcYhvExWPAzDMP4GCz4GYZhfAwW/AzDMD4GC36GYRgfgwU/wzCMj8GCn2EYxsdg\nwc8wDONjsOBnGIbxMVjwMwzD+Bgs+BmGYXwMFvwMwzA+Bgt+hmEYH4MFP8MwjI/Bgp9hGMbHYMHP\nMAzjY7DgZxiG8TFY8DMMw/gYLPgZhmF8DBb8DMMwPgYLfoZhGB+DBT/DMIyPwYKfYRjGx2DBzzAM\n42M4JfiTk5OpQ4cOVL9+fYqJiaG5c+eaths7dixFRkZSbGws7d2715lbMgzDME4S4MzFgYGB9O67\n71JcXBylpaVRkyZNqFOnThQVFfVfm8TERDp27BgdPXqUduzYQSNHjqTt27c7PXCGYRgmfzi14q9Y\nsSLFxcUREVFYWBhFRUXR2bNnpTYrV66kwYMHExFR8+bN6erVq5SamurMbRmGYRgncGrFr+XkyZO0\nd+9eat68uXT8zJkzFBER8d9+lSpVKCUlhSpUqCC1mzhx4n+f4+PjKT4+3lVDYxiGKfQkJSVRUlKS\nS/pyieBPS0ujfv360Zw5cygsLMxwXggh7VssFkMbreBnGIZhZPQL4kmTJuW7L6e9erKysqhv3770\n8MMPU69evQznw8PDKTk5+b/9lJQUCg8Pd/a2DMMwTD5xSvALIWjo0KEUHR1N48ePN23To0cP+uKL\nL4iIaPv27VSyZEmDmodhGIa5c1iEXg+TB3777Tdq164dNWzY8D/1zZQpU+j06dNERDRixAgiInry\nySdpzZo1FBoaSosWLaLGjRvLg7BYDOoghmEYxjrOyE2nBL+rYMHPMAyTN5yRmy7z6mEYhskP588T\nzZpFlJ1NNHYsUfXq7h6R98MrfoZh3EZGBlFsLNHhw9gPDyf6+2+iEiXcO67CgDNyk3P1MAzjNo4f\nV4U+EdGZM0T797tvPL4Cq3oYhnEb4eFY3V+7hv0iRYhq1FDP//030ZIlRBUqED3xBFFQkHvG6W2w\n4GcYxm2UKEG0ahXRhAnQ8U+ahMmAiOjYMaKWLYlu3MD+b78RLV3qvrF6E6zjZxjmjvDzz0RJSURx\ncUQDBthvP38+0ahR6n5AAFFmJpFJ4L9Pwl49DMN4NN9/T9SnD5Eip86dIxo3zvY1tWoZ91nouwY2\n7jIMU+AsX64KfWXfHvfeSzRtGlHNmlD5OHIN4xgs+BmGsUpOjiyw84vZ6l0Ios2bof7JzVXfCp58\nkujyZbSbMAGeP1u3EtWv7/w4GMA6foZhTJk2jejVV4kCA4nef5/oscccu+7GDaLUVKJq1XAtEfz1\nn3iC6NdfIcBLlCDasAHtiIjatCHaskWdZCwWorAw6PkHDXL5V/MKOGUDwzAu5a+/iBo0UPcDAqCX\nL1vW9nWbNxN17w73zIYNIejLlJHb3HMP0fr1jo0jIIBozx6imBjW7+vhAC6GYVyKompRyM4mun7d\n/nXPPKP65O/bB9WNPiBr1y7Hx5GdjQmkSxd49DCugQU/wzAGmjcnatpU3e/aVQ6ssoZeOG/aBMPs\nwYPqsfbt8z6etWsRyMW4Bhb8DMMYCA6G0XXxYgRN/fCDY6qW1183RtempyNIS2HxYqJnnyXq1i1v\nY5o9m+juuzEWxjlYx88wjEs5eRJ6/OPH1WPLlhH17Uv0779EQ4ZA/dO5M9GpU0Rr1tjvMyAAah/l\n89690Pv7MmzcZRjGozh0iGjgQKRdqFsXPvjVq2OVn5iYt76KFzfaF77+Gv37MmzcZRjGY3jtNaIW\nLYj+/BNqnj17iCIjiWbOJFq3Lu/96YV+UBDR779DrXTmjGvG7Gvwip9hGIncXKJLl+CG6ZfHpeGP\nPxL16FEw41KoUoUoJQWfq1bFBFOyZMHe0xPhFT/DMC7hxAmiOnWIypcnio4mSk527DrFm+fFFwtu\nbEREpUqpQp+I6PRpot27C/ae3ggLfoZhSAhEzg4frhplDx+GOoWI6MIFom++QRuFr78muu8+osqV\n4QVUty7y5xcENWvCl79nT/ktJCAAEcJM3uDsnAzD0COPEH31lfF4WhpW2M2bE509i2NTp0LvPmWK\n3PbIEdn7xpWkphL98498zGIh+uQTotq1XX8/b4dX/Azj4xw+bC70Q0KQOvnrr1WhTwQj7bRp5n2F\nhVm/T3Q0dPL5IT3deEwIpIQggqpp8GBU6urYEeklGOuw4GcYHyc42Hhszhzk62nd2lj4vFgxZO00\no1Qp6/c5coToypX8j9OMzz8nun2baNYsoi++gErq11+JRo927X28DRb8DOMj7N6NlMcLFsjHq1eH\nC6bCc88RjR2rpmho1w4qHIXz54keeMD8HidPWr9/drZaRtFVhIQgA+ipU/Lx06ddex9vg3X8DOMD\nJCUh3YHi/bdmDdGKFer5unVhQA0MREStlh9+kPX2N28iIMvPD66fWu6kV3aRIkSLFhH5+xP170/0\n0UfqeHw9uMseLPgZxgeYPFkWyitXqp8PHYJ+XBHuPXtiBV26NPYDTKREQRhw88LKlQgKq1oVE9hH\nH0EFde0afPrvuce94/N0WPAzjBeRlUX0xx8QfpGR6nFFiCsownzbNqzwtYI8LQ0CdcECFEHZvLng\nx50XAgKIevXC6j4wEGPXTmpXryI9tKM5/30R1vEzjJeQkYGVbrNmUN3MnKmeW7gQQVlEcIOcPRuf\nR440z7Ofng4Xzx9/hMHUk8jOVlU6WVnm6qW0tDs7psIGp2xgGC9h6VLZ6Ornh9QLSjqD3Fz45Cue\nNw88AF2/rT+9e++FvnzIkIIbt6sJCCD69lsUgfFmOGUDwzCGvDq5uUSdOmFVrJyvWhW68LfeIlq9\n2r4xdv16vEG0bl0wY3YlxYsTjRqlVv5irMOCn2G8hJ49kRVTy65dCNBSWLcOlawcTa2Qk0P0wQfm\nvv6exvXrGOuECepkx5jDqh6G8SJOnEAKA0UHHhQEn/Zt24heeEGdBAIDHReOQUEosq6N3vV0WrXC\n20qRIu4eScHBqh6GYYgIQVeLFhFVrIjkaV9+CXfNPn3klX9eVsSZmZ4t9IsXNx7bupXo++/v/FgK\nCyz4GcbLePRR5Ko5c4ZowAC4Y3rrC7XFQjR+PKKP9ZjFHzCAVT0M4+UMGYK3AGsUVEZNdxIRgWye\n3iz8ueYuwzBWKVbM3K89OJioXDlEu7o6h447sVhQ11efesLbYMHPMIxVAgKsZ9P0JqpUgfvqY48h\nsZy3w8ZdhmGIiGjVKqJu3YgeflgtURgY6N4x3SlSUqDS+vlnd4/E8+EVP8N4Cfv2ETVpourrGzZE\nIfLoaKKDB907tjuJxYLv3aCBu0dSsPCKn2EY2rtXNtLu20f04YcoW6hn+PDCEZSVH4SAH//Nm+4e\niefCK36G8RIOHCBq1Ah+97YoXZpo/36iy5eJGjf23ijXQ4eQrM5b4RU/wzAUHQ1vlm7dzM8HBhIN\nHYoJonJloqef9l6hHxiY//q+vgCv+BnGy9i/H/p9PQEBsqCvVQu+7t7Kpk1Ebdu6exQFB6/4GYb5\nj+hoog4djMezs4nmzUM+nwsXoOrxZrx5UnMWXvEzjBeSkYHUy/qSi75CqVLw7ImIcPdICg5e8TOM\nl3L9OgqJV6+Oili3bjl2XXAw0RtvFK4CKq4gLAwlJ1ev9m6h7yxOCf4hQ4ZQhQoVqIEVh9mkpCQq\nUaIENWrUiBo1akSTJ0925nYM43M8/zzRsmUofr54MYS5I6SkIA1z2bIoThIfb72tv79LhuoRpKUR\nHT1K9PLL7h6JZ+NUCqOEhAQaM2YMPfroo1bbtG/fnlauXOnMbRjGZzl+3Pa+Gdevo2LW6dPYr1yZ\nqE0b8xz8RYoQ3b7tmrF6EuvXE23cSNS+vbtH4pk4teJv27YtlVIKeFqBdfcMk3/69pX3e/e2f82+\nfarQJ0Iu/aVLVaFfsSJSOvj7e6fQV1i61N0j8FwKNGmpxWKhrVu3UmxsLIWHh9OMGTMoOjq6IG/J\nMF7FiBHIoLlrF1btXbvK58+cIQoNVQuqE8EeEBwMA68ZQkDoe3vitmrV3D0Cz6VABX/jxo0pOTmZ\nQkJCaPXq1dSrVy86cuSIaduJEyf+9zk+Pp7ibSklGcaH6NPHWDw8N5fooYeIvv0WKpwFC4gSEnCu\nShWi//0P9gGzHD2pqUSff25+r+LFoSoqzISF4c1o/Hh3j8S1JCUlUVJSkkv6ctqd8+TJk9S9e3fa\nv3+/3bY1atSg3bt3U+nSpeVBsDsnw+SJn34i6t5d3Q8OhmFTW3jk6lVEr3pTrn1rREQgKVvVqhD4\n3pyqQcFj3TlTU1P/G9jOnTtJCGEQ+gzD5B29bj4z03hs61Z49NSu7VifFotrxnYn8fMjGjkSnk/b\ntyMpXYMGRCtWuHtkno1Tqp4HH3yQNm7cSBcvXqSIiAiaNGkSZf2/BWnEiBG0bNkymj9/PgUEBFBI\nSAh98803Lhk0w3gDFy8SpafnTxfdrRtR06ZEv/+O/TJlUGmrXTuilSuJXn2V6L338tZnYXzpDgiA\nWmfWLDUSOSsLeYj+/Zdo0CDYQBgZjtxlGDcwfz7RmDEwsA4cSLRkSd5X3LdvE/32G3z7N29Wjz/+\nONHChbADOIqfX97aFxaaNcMz8sZiNFx6kWEKEbdvY3WuzZ2/Zg3Rffflr782bYi2bFH3fcFjJy/8\n8QdRbKy7R+F6PFbHzzCMkZwcWegTOedPP2oUVuxELPSJ1GdBBFVQ2bLuG4unwoKfYe4woaFEL76o\n7rdpQ9SlS/77e+ghGDY/+QR5fczQ+vl7M35+RG++iWIzZcrgmYSHu3tUngerehjGTezdC5/5li2J\ngoJc0+f581AZ7duHQK6EBLg2Dh5sPaDLG6haFRHJL7zgWHSzN8A6fobxMtavR6Ixi4Xo7beJTp6E\np05QELx19BG8eq5cwSpfKTzeuLF3Gm8VgoOJ3n0Xrp2+Agt+hvEiUlNRHSs9HfuhoSgcrvyJhIQg\n/06JEuo127djcoiPx8pX4dIl9HXt2p0avfvw80OOIl9R7bBxl2G8iFOnVKFPhM/av++bNxEDoDBn\nDtRFDz5IFBeH64mwwh861DeEPhG+r698V2fhFT/DFAC7dxNNnw7VzOuvY9WtPXf8OIy6lSsbr01L\nI4qJUQV4zZr4Vykl2LIl/PaVPPpVqxIlJ6vXjxyJN4LkZKI9e1z/3TyVTp3gFuvnI8tZVvUwjAdx\n/jxRvXrq6rNaNaLDh6GHXrgQAVZCwOtk2zZUjNKTkgKdtZ8f0VNPIQBp0SJMJMOHy9GoDRoQ/fWX\nuh8SgrcCXyAwEBPfwIGYYL0xUMsaLPgZxoP45ResPrUcO4ZVf716mAQUXnyRaMoU5+63bRtRz55I\nUdCiBfT9vsCkScgyqrwJvfwyagz7CqzjZxgPIjoakbkK4eGqwVFrkCVCGmRnadmSaMcOePs8/7xv\nBCz5+RGdO6cKfSKid97xbs8lV8IrfoYpALZtI5o6VS16Xq8eju/eTXT//VAHdehA9OOPRAcOwP2y\nXTuUQrRGejreDlJSYMjt3BnHjx4lat4cfRARjRuHGIFNmwr2O7qb8uWJLlxQ94OCvDtWQQ+rehim\nEJGbCwNu8eJEr7xC9NZbON6kCYR1SIj5dX36qOmG/f1h4G3ZEioPTR0jCg9H9OoXXxC5qG5HoeCe\ne4jWrXP3KO4crOphmEKEnx9R0aLIof/22+rx3bvxBmCNX39VP+fkqCt6fZWtixeJhgyB0A8Lc9mw\nPRIl4rlaNaKPP3bvWAoTLPgZ5g5y+TJR69YQWE2aGL1Qiha1fm2jRvJ+XBz+Vdw+FbTqjrS0/I+1\nMPDMMzCWHzqEFBWMY7DgZ5g7yBtvoDIWEVwwY2NV4T9gAPT/1vjmGyRka9eO6KOP1DTOEREFO2ZP\npXx5qMtKlrRtG2GMsI6fYe4gjz5K9OWX6v7dd0Nvn54OQXb+PFG5cnlL2nbuHPzY//wTbqStWxNN\nmIBKVL6An59aYL5ZM3eP5s7Bxl2GKSRs2kR0771Qx/j7YxXfrx/y89xzD94CKlVCBGrDhrb7+uor\notmzseKdMwdupArFi/tGkXUtISFQbRXG2sH5gQU/wxQiDh6Eu+epUxDeISFw9/zf/9Q2lSohGGnI\nEPM+9u4luusu1W+9WjUkaVPONWlSOGvoOsvff8sToDfjjNx0qtg6wzB5JyoKXjnDh6uCWxvNSwT1\nzdChOD9smLGPLVvkYKVTp4jGj4e658QJ3xT6RFxY3VHYuMswbuDUKVlwZ2aaV8lav9547O+/iV56\nST4WEgJ1T1KS0cvHV5g4EW8+jH1Y8DOMG2jRQs4b37o1Inh79JDbKS6bWVlEiYnIA/Txx0b9va8k\nZbPFgAHuHkHhgXX8DOMmUlKIPv0Uq/WRI6GmuH0bHjm7d6Ooyhtv4M3g3nvVKNyYGDkbJxFSQ/hS\nugI9QUFEZ874Rp4iBTbuMowXs3kzfPe1REYiR4+Wxo0dz79vsXiXHaBCBai4goPdPZI7B6dsYBgv\nxiztgjYrpYJe6Ntya/QmoU8Ed9jjx909isIDC36G8XAaNYL6R0tOjv3rrCV7s0VhLWRSrJh5NTPG\nHBb8DOMmsrLgtbNtm/2206ZBlaPFlmCvXJmodOn8jamwoC2xWLly4Z203AELfoZxA1lZMNjecw9R\nq1ZETz5p/5offiDq1QulBuPjkdLZTJ0TFkb0/fdI2ezNaN1hDx9GMBzjGCz4GcYGu3bBw8bVbNgg\n58p//32UTrRFlSrQzZ8+jWsnTkS5QS2BgQjiatoUidzKl5fPe7Px01eKrLsCflQMY4VHHoEAvesu\n66kT8os+/bK/P1wSr18nmj+faMEC1Tdfq35Zu1b9nJmpVt1SyMpSUzdcvixXqCLyXpfPli2RuZRx\nDHbnZBgT9u1DymQtBw4g3YKjrFuHJGwREaiFe/AgjkVFIVDr8ccRjOXvTzRrFoT07NnI1EmETJNF\nixJt3EhUpw7RTz9BuO3apd6jaVOi33+X7/vNN3BtXLbMeM4b8POT1Txvv0307LNEAT6WgMYpuSk8\nAA8ZBsP8x99/CwHFirodOeL49Vu3CuHvr17bsaMQgYHq/vTpaHfunBCXLwsxZ47xfvqtSxchTp0S\nokcPIZo2FWLyZPN248fb78ubtvLlhfjhh4L5f+DJOCM3WdXDMCZERxONHavuP/ssgqYcZcMG2eVy\nyxZZZaPk5K9YkahUKaI//rDf56VLMOz+8APRzp3WVRuzZzs+Tm/gwgWka0hOdvdICg8s+BnGCnPm\nIFDq5Emi6dPzdq0+l742Lw+RsWrW3Xfb73PUKHm/Rg2iMWPUfXvGzVKl7N+jsJKRAaM34xis42eY\nAmLePKIlSyDkp09HRs3ERKKaNYlq1cIbwdixajqGxYthA2jYEIbZKVNwPDAQPvt16+JNoU4d+T5/\n/02UnY1JYPNm87GUK4c0zytWGFNAewPVqhHt349ALl+Bc/UwTCFBCCRZO3AA+0WLQmDVqmVsu2YN\nDLSffKIea9oUah4zNm8m6tbNmLkzIAATAxFRiRLI+Ll1a+EK1lIICyN64QWin3+GAf7mTXg3lSsH\njyd9QXpvhnP1MEwhQAii0aNVoU9EdOuW9cRqnTtDnaPFVq79tm1RhEVfsF0R+kRE167BSygrq/D5\nvUdG4k3o5ZfxHUaOhNAnQgzEU0+5d3yFiUL20zNMwfHRR0Tt28N/314wVX746iv46GsJClJz7pvR\no4fs8//AA7bvUbo0cvY7gtYlsjBw9Ch+IwXF7dXaPmMdH/N8ZRhzEhOJRoxQ91NToU5wlvXriXbs\nQKEVs9V6QADKLFrzGAoJIXrwQaJjx6D7t5faQQjk9PdWtAFpI0diMr10Cc/xhRfcN67CBq/4GYZQ\noNzWfn5YvBi5eF5+mahDB6zc9YnVbt4kevFFGHqffx6J2B57DHr68+cRkfrpp0SbNsFYHBVF9Npr\n1u/57bfW0zFXr+78d3I3WtVXvXooSLNyJewkgYFE/fsTjRtHdPWq+8ZYGOAVP8MQome1xUni453v\nU5s0TAj48u/YgTeLrVvVc7m5cB195x3s792L8XTtalQ55eYSvfkmvHtiY5G1s2ZNCL2cHHjuWLP3\ndeqE6w8fhj3g++/xWVH5+Ps7lu7ZnSQkEF28iFQVcXEQ9N2743n27i0Xr1+zxr1j9WhcEEDmNB4y\nDMZHefVVNQo0MFCIxx8XIj3d+X4ff1yOMB03DsdPnRKialUcCw0VYt06IQYNktvGxQmxd68Qfn72\nI1eLFhVi6VIhbt8WwmIxbxMUJMSsWep9Q0KEWLlSiAULEGFssQgxdCjG4+5I3Lxsc+bgmc6YIR8P\nDXX+9/N0nJGbHiFxWfAz7qRyZVlovPmma/q9dAlpFkqXFqJ7dyGuXVPPXb8uxPbtSNkghBA9e8pj\niIzE8U8/xeeAANsCMCREiOxsIUaOdFxoVqjg2MTiyVvbtnhOSUnypNehg2t+Q0/GGbnJOn7G56lU\nSd6vWNE1/ZYuDaPxpUvQQxcvjuM5OUir8PrrRB98AHdLffpkpWh4QgLRkSPoo1s3RN+a6fBv3YKL\n5qOPOj6+1NTC59mjp2ZN/Nu+PVRrnTsjk+rSpe4dl6fDOn7G51m0CLleTp2Cu2RCQsHe7513VAPt\n2rUQ5EOHwhh86xb860ePlq8pXhzZOYngw/7ZZ5hUFC+X0aOJihQhatCAqGRJ3zBu1q4NW8WCBZgc\ny5QhWr48fyUnfQ2O3GVcwp9/wp0uIwNeLB07untEeUMI5HopUQKCsyDp3RuGVYX77oMh8sgRGIBj\nYhCha48bN+ByWrKk+ryXLCEaNEhtU7o0vF/KlsXbwjffeEdO/rAwCHq9i2znzkSrV7tnTHcaTsvM\nuJWbN6EvVvSrRYsKcfq0u0flOJmZ0MUTCREcLMQ33xTs/aZPl/XUb7zh+LW5uUK88ooQ9evDLnD+\nPI7fuCHExo1CvPyyUQ++YYN6fUSE+/Xyzm716gkxc6b185mZLv25PBZn5KZTEjchIUGUL19exMTE\nWG0zZswYUbt2bdGwYUOxZ88e80Gw4C/UHDtm/ONbt87do3KcxYvlsZcoUbD3y82FF0rv3kJMnSpE\nTo7j1376qTzWbt2ESE0VonZt7AcEyHUAiITo2xfXXrniuHC15h3kCVt0tBA//WR+rmbNgvnNPBFn\n5KZTxt2EhARaY8NZNjExkY4dO0ZHjx6ljz76iEaOHOnM7RgPJSJCTjscFmasXuXJ6FUfmZkQIwWF\nxULUty9USx99hHq7jnLokHF/4UJE9hLBUFykiNxGMSoXKwZVlh59ymhljJ6EtrpWmTJIYz18OPaD\ng5Gds317oh9/dM/4ChtOCf62bdtSKRtJvleuXEmDBw8mIqLmzZvT1atXKTU11ZlbMh7I7dtInqWQ\nni7vezr9+8v58994o+AFX1wcirj/8w9SMzsqsLp0kZOrdeuG4C0tFSuqJSLr1yeaPBmf/f2JZs40\n9nnmjPGYJ3n7hIYSPfecur95M6JzP/oIkc/p6aiZkJSEAjqMfQrUq+fMmTMUoak4UaVKFUpJSaEK\nFSoY2k6cOPG/z/Hx8RTvitBJ5o5w6RK8URSEgDCpW9d9Y8oLxYoRbdtGtH070vs2aFCw97t9G1ky\ntSxfjghUe8THw6C7ciX2z52DkbdhQ6QpDg0lmjsXBs4TJ3Du5EmiypXRvnNnOUK5MFCuHNF778nH\ntmzBv/qi9d5MUlISJSUluaSvAnfnFLr/YRYrSymt4GcKF9WqIQmZ8sdYq5ZjXimeREiIY1WwXEGR\nIti0ydTatYMwv3ULaZVDQ61f37Ej1GuxsWofsbFIU1CuHNGvvyKvDxHUSQ8+iKygn3+OfguT0Pfz\nw8Slp3btOz4Ut6NfEE+aNCnffRWo4A8PD6dkTSHMlJQUCjdTKDKFGj8/+KN/8gn05Y895luVkPLD\n+vWIHUhLQ9DVunVwtSRCMZEtW8xXs4cOEc2ahdW8duL480/o6kNDEZil5dw5pHd2dR4eP7+CVQmF\nheH5mNFLSelBAAAgAElEQVSnT8Hd1ydw1rJ84sQJq149q1atEl26dBFCCLFt2zbRvHlz03YuGAbD\nFFrOnTN6p6xZY2x38aIQZcqYe7NERantkpOFKF9ePdemjdxWm/6hb9/8e9cUKVIwXjvNmglx5gzy\nJXXqZDxfvLgQJ0/eud/HU3FGbjpl3H3wwQepVatWdPjwYYqIiKBPP/2UFixYQAsWLCAioq5du1LN\nmjWpdu3aNGLECPrggw9cMFUxnsjkyUTNm6OIyZUr7h5NwXHuHLJmRkYSPfusa9QmoaEoyKLl3XeN\nq91582BP0VKzJp67YhxOSYGq6MIFvAHExyMds1bD2qIFvkdyMvL7m5jcHOL2bQSHKZlNXUXz5rBJ\nhIQQtWqlHi9WDOkYNm2CepFxAhdOQPnGQ4bB5BO9b3n//u4eUcGhBHop20cfuabfL780+t+XLCnE\nP/+obUqVsu5r368f2gwcaL6KDglRr5kxQ4idO4Vo0sT9PvnaLTRUiKeeEuLWLfU7BwXJbd57zzXP\n2xtwRm5ykjbGafbtk/f373fPOO4Eir+8wtGjxjZJSURVqmDF6mhVqIcfRt4ZLVevIpHbtWtYySv1\nZRW0bxvLlsG1Uf9GoHDzpnrNK6/AQLx7t2NjcxXlyiGmwN/f/Hx6OtHbb6PwTL9+MODqvzPjGljw\nM07TqZPtfW+iZ0/1s7+/sbA5EeICzpyBh860aTB865k7Fz75zz6rusJ27mxsd/gwVDEREci1o6Av\nwh4cjAItjzxiXbAqZGbCzfNOc/kyEqpZ87WPjcXzGD0a7q3HjxvbdOlSsGP0GVz45pFvPGQYjBOs\nWIFCHu+8I0RWlrtHU3Dk5kK989xzyI2jJzPTmO7g88/lNosWyecffxzHR42SjwcFCREWZlSJDBwo\nxP79Qjz/PAyd2vu1aSPErl1C3HWX0SCqVw+5Y7NYzMdQvz6M17ZyCT38cIH/vIUKZ+SmR0hcFvyM\nNzF4sCqswsORS0fLE0/IAi02Fsc7dJCPN2qEimBmwpMI3jlDhxrP//CDccKYPl2IJUvMvWQ8YQsI\nEOL334W4+27juYgIeDnl5t7xn9KjcUZuclpmhnExublE//sfVBvp6aizGxND9NJLSK+weDFUMgqj\nRiFfz6xZRM88k7d7mfnSly4tp8zo2xfBYVlZ8B7yVL35zJmIbRg+HCquMmWQf+fZZ9XiOIcOIV3D\nlStEY8bIz9HXcEZusuBnmALiyy/liljjx8NNkwi67jVroO9+7TXo6ImIvvgCuWgWLpT7qliR6Px5\nxwqi69sUK+YenX5e+ewzov9P7WWVWrWQ34gIk96OHUR33VXgQ/NInJGbbNxlGAfR5iNyhM2b5f0N\nG9TPI0YQrVhB9NZbqtAnQhGVDh3kY0QQ+kTmQl+b42fyZCJtEtzq1Y1J3BT8/BDxu2gRvJDyQoAu\n5j8mBknTHMUsJYVSblLPyZOojHbvvarQJ8KbzsGDjt+T0eACVZPTeMgwGMaUY8eEqFMH+uYWLVBE\n3RE+/FDWVZcogSLr1sjNFaJXL1nvrfdj1xtou3fHdUeOyMVvVq0S4rPPYISuXNncoBofj7YZGfkr\nut6xoxBVqqAmwJkzQvzyi+PXbtokRMOG6n65ckZbiILy7PXfPSxMiOPHHfstvBFn5CbX3GUYOzzz\nDMoiEiGD51tvmac31rJhA/LpaLl2DaqJe+4xv+bMGbkkY3Y2VBt6t0bt231oKKJmIyPlNu3aocTj\nL7+ox0qWJGrZEmOrXx+qFSK8ReRHY3DzJqJ/MzORH6h9e+jo7RU6r1QJaaM3bMBzvHkTdg6l4HxW\nFmweZ8/ibUZ59sp379ULkb3DhqnF1pk84sIJKN94yDAY5j9SUuBeKIQQ7drJq9WEBNvXLllivsL2\n8xPiwAHr1125YvTiiY62vXI2S3+VmytE69bm7a0UwRPPPWf7Pn5+KKmpPVa8uBAHD2LVTyREZKQQ\nffrIbcqVM++vd288Y2XFro3WffBBtV3RokLUrSvvHz1q+/n7Cs7ITdbxM4yOhATovMuXx8pzzBg1\nKCokhOjxx21fv3ixvIIOCYFxdv58tUCKGSVKEA0ciHv5+yMga948NdNptWpG3bq2sLrCuXNqimwt\n/v5yta2lS5H7ZuZMrNZtkZtrtHFER8NTKSUF+0ePGiuEtW0rG7gV1q9HUFqtWnjWRYvi3717iX74\nQW136xa+48iRSC/988++mZLZ5bhwAso3HjIMhhG//iqvTP39oZffu1eIL75wbLU5fLjcx5gx5u3S\n0pBJU/FPf/NN+boFC3D8yhUhBgxQj4eHw8f/k09wPjcX/aSnY//mTeT50X8Pi0WIChWEmDRJiG+/\nlc/fc0/edfxlysj6dyIh2rYVomJFfK5aFW8477/veJ9NmyKuQXvsp5+c+029FWfkpkdIXBb8jDOs\nWiXExIkQ2s6SmGgURo4acxUuXhTi3nthzO3aVYirV41t1q5Vg6yaN8c1+gCuAQPQdt8+45iOHMG5\ntDQIW0X1sn49jiclCRETg+LjrVoZr9caVhWVkpLIzZVbZKQQM2c63r52bXy39u0xqUydmu+f0uth\nwc/4LB9/rAoNi0WI5cud6y8jA0JH6XP8eJcM00CtWrLAK1YMKQm0x6ZMQds//zQKyEOHcG7WLPl4\nvXo4npsrxLRp8NypUMF4feXK8n67dpioXC34ieTnabZp6wPMnClE5874LSMjYUNgzHFGbrKOnynU\nKFWriCA67HmU2CMoCNWw1q+HB44ScJVfDh5Etahu3ZBHXkGvL79xQ9VtBwXBc2XnTmSptFhQ1Uxh\nxAi1nrG+HyUL57x5RM8/j0yh+opcRETNmsn2gs2bjXWAiRA96yzh4UbbhJaAANg/tmzB91mzBr/l\n0aPw9mFcDwt+plBTvbq874oCHYGBqL/brJlz/dy+jUylK1YQJSaigItSiXTsWGN7Jbo2M5No1Sq4\ndi5fjhTKs2Yh2Gr/fqIPP1SvSUggqloVny0WGFKTkzFp2eLyZbiLKghh3q5UKeef6TPPYGJp2NC8\nnOTt26gN3KoV0cWL8jn9PuMaWPAzhZp33sFqukIFpEN+7TXX3+PcOaIJE5AzRlNC2qHrzpxR99PT\n1UhTpWKWNbKy1M///ouV94gR6FNLpUpEf/yBfPx16yJyt2ZNY0UvPZs2ma/C9ZW0jh0jGjoUPvP5\noUULosaN8e+ff6qpmfUonkuDB6PWrsLo0fm7L2MHF6qc8o2HDINhDNy8CYOjooOuVs129K2WjAwY\nV5VrS5ZEfd2sLPNIWcX3PzAQOn9rOvHnnzfea84cuU2FCkKMG2es6mVvM8ve2b27EI89Jh8LDZV1\n89a2XbswvtRUjGfAABjjH3lEbVOrlpx58+hRIRYuFGLzZqd/Pq/GGbnJK36GscGRI3LVrVOniA4c\nsH9dbi7Rrl1Es2djxTxoENGvv2J13qaNUbXi7w9/+uXLUdFsyxbkpwkJMfY9YwZW0F26qFGthw/L\nbS5exNvPv/+i0tahQ47py8uXN8Ya5OTA315L3bqyqqhIEWMlNiKor5o1wxvZnDmwwfTogVq/J0/i\nmmPH5DeN2rXxzNq0sT9eJp+4cALKNx4yDMaLuX0bXjIjR5oXULHGxYvy6jskBKt2W+TkCHH//eo1\no0bh+PHjQgQHW18dV6pk7GvqVNsr6ho1hBg92vycEgeg5ccf5Vz9+mjcl182ruTvvx9vL8OGCVG9\nOvIJ6fMQNWxo7jbavbv52N591/HfgDHHGbnJK37GJ0hIQJTp/Pkwlu7a5dh1ZcpAH9+iBVau33+v\n5oa3xtatRD/9pO5/8AGiWw8fJsrIsH7dhQvG7Jv2smaeOIHoYjP0+noilIrcsYOoSRNkw9R7BX3/\nvbySJyKKi4PN4O67sbI/cYKoTh0YqEuVImrQAG8rW7fK19nKo9Owoe3vxRQsLPgZn2DNGvVzdrac\nvMwe7dsTbdsGgelIPWF9GmSLBccaNTJX3SgULSqnKyAyCtO8sHq1+fGff4b6x8xjRp/m2N8fAvzo\nUXgMHToEI23v3kRTpsBYu28fjMz6iWbJEtXtVI+1FMzMnYEFP+MT1K9ve99Zjh5Vs3E2b44qUgpv\nvgkdd8WK0G1rKVECefGJiNLSkKvnwgX1fIsW1u9pb9X899/mx7XZLongUdOkCVG9esZqXjk5+C67\nd8tvAteuwX6QlobsoS+8INstKlYkio8n+vZb4/2DgvA8GDfiQpVTvvGQYTBeTHKyED16IMfNzJmu\n7Vtb9/bFF9XjJ08Kcfas3PbiRTW/jZ+fECNGGPXfehvE++8j5314uNwuLg7ePKGh5nr0gQPhSTNp\nElI7KKxaJWcPvesuIR54QIiyZa3bEqpVgw1Ce01SkpoTyFa6B60doWRJIf73P9c+f1/FGbnJpRcZ\nxgl27SJq2lQ+dvo0Mk9a48YNot9/R5TtoEFE16/L5zduRD79XbvgBdSgAewTv/4qt6tXD6qZq1dR\nteuPP7CabtKEqHVr2DPS09G2UyeoeIgQ0fvOO/gcFoZVOxFUNbb+DO+5B3YOIaDf79kT0cV6bJWH\njIpyzCuKsQ/X3GUYN7Fjh1Edc/Kk/WjXzExE3JqlU4iKQkHxUaOgejETyBYLSh0qgVWZmUQff4wo\n2YwM6Nz1wV6ZmThma2wVKmBMAQFGI29MDALSrlwxv7ZMGaKXX8ak99BDchCagp8fjvuxktlpuOYu\nw7iJZs3gb68wZoxjKQ42bDAX+kRYxT/xhKpv1/9tFyuGNwZtNG1QELx7FK+hc+eMvvGBgbZX9ETw\nnf/jD6PQJ8J4rQl9IqJLlzBhxMcTlS5t3ubee1noewL8EzAuJzMTKQSWLzdf9XkTFgvR11/D+Llv\nH9HcuTj+1ltYuXfqhDcAPWbFxh3Fzw/qHHu0aAFXzI4d1RQR1aqZ5wlSWL5cNfTqsSX0FbKykDbC\nbFLr2hX9Mx6AC2wMTuMhw2BcQFaWnFe+UycENPkS330nGzfNyiOmpaGQidKmalVjMJWy6dMu+Pkh\nsKtkSZQ9XL0afU6cKLcrWVJNhZCSgqCrH37A/l9/CdGkie3gMG2glyNbvXqoXZCQYH6+bt078/x9\nBWfkJhdbZ1zKvn1QYyisWwdjXkyM+8Z0p9G7S+r3iZCt8tIldf/0aejPR4xQg7/KlEEbvaG0aFG4\nTxLBsDtgAFwr9WkVrl3DCvzCBSRK+/dfHI+MhJpI77qpRzH66ilWjOjhhzGO8+fxthMWhuRrpUuj\nTOLSpaphWUEfLJYfMjIQk1GkCNRGZkFqjAO4cALKNx4yDMYFHDsmuwr6+Qlx+rS7RyXE/v0oQB4V\nBffIgmTvXjk1w+DBxjY7dsir4eBgIW7cECI7W4hffoF7pTXXyBdeMB4/ehRFabRFV4YMQcEW7ZuF\n2RYUhCpe+nKN9rZmzeTfukYN9fv9848Q8+erBV/8/NRSkVouXxZi+3bHqpxlZMhF5B96KN8/kVfg\njNz0CInLgt+7mDkT+V4CA4WYO9fdowHVq8tC67ffCuY+587BT375ciGeeUaI2bOh/jLjtdfwnEJD\nhfjmG/X4gQNGIevnJ8SKFcgWeuUKhKxy7t575Ype992H+x89Cl9/R4T4tWtC7NljO5eQI9uRI0L0\n6QMB/fnnGOuaNUL88YcQmZny9//zTzV2oFQptLHF+vXG+yUnO/d7FWZY8DMeR2amdYF3p8nIMAqM\nRYtcf5/9+4UoXVpdwScm2r8mO1tOSSwEBKCZUI2LUwOxLlxA8NYnnyAZm34Fv2mT40K8USP0+dNP\n1tvcfTfelLQrfCI5eCw+XojGjdV9iwUT7KRJmLiCgvBWotCvn9xX48a2n9Xvv8vt/f3zXg/Zm2DB\nzzB26NJFFRjFiwtx4oTr7zF8uCyY2rXLXz+5uYiMNRPAinFWy7JlcpsyZYxCVb+VLIkav6NHI1e+\n2fiJsHLftg3n9+2T3zRefBFqrTFjhHj9dbw16A3RL71kFNapqTA0ayOBlbcae44Azz+PtgEB6MOX\ncUZusjsn4xMsX040dSoqaW3daizZ6Ar0ZQXNygwSoYpXixZw6ezVS62TSwQR2KmT9eyhxYsbj/Xu\njQRqRDC8fvEFjJ+2qFOH6MsvUZu3eHG4atauLbeJjES0b4sWRAsXEsXGqvmIiNA+Lg6xCzVrImfP\n3Xer54OC0IeWnByiV15BnII+wMzf3/aYifAb3riBbcQI++0ZK7hwAso3HjIMhnGKc+eEiI7GirRS\nJeiwzejdW17pvv66eu7nn62v0iMjhfjyS7mvGTNwvE0bIXbvhttmt26o/BUYaN5PhQrIu5+RIcTS\npUIUKYLjDz0kxBNPwF7QsyfyCgmBdmZ9Va8uxJYtap4ef3/o9Z9/Hi6dGzfi2pYt1Wt698Z4zcbl\nKfagwoIzctMjJC4LfsZbyMqCF9Pt29bbNG8uC7zhw9Vzq1YZBWLx4vL+Z5+hrX6SiIoSomtX+Vjn\nznKZR22RlR49jL76K1YYx3vzplG3r2xaFRoRvIP0pKVhcps6FTaNbt3ka15+GUVqmLzhjNxkVQ/j\nExw6hFiCIkWs55FxBQEByFUTHGy9zWOPyfvXrqmfO3WSo2ZDQ43pE+bNw7/akpDK/tGj8rGYGOTl\n79cPqRS0fa1cafStN/PdL1oUSeLMKFXK9n5ODlH//kSTJiH2YMQIqI26dYO66bnnkLbaVtEWpgBw\n4QSUbzxkGIyLWbsWXhye4HKnLws4Z86du3d6uhDTpwvRoIEQ9evDjVO/glaKkguBt4bPPhNi1iwY\nQvV++B06oN2RI/KKvV8/IZ59VjakJiWh7ccfG1MnBwcL8dxz6n79+jDQajl1Soi+faFKeuMNlJFU\n3iBGjYIfvvJs69RBHIeWzZuNbwknTxbcs/YlnJGbnJ2TKRAmTSKaOBGfy5ZF+t4aNdw3nlq1iP75\nR92vWZPo7FlEtM6Zg2jZokWREbNYMdfdNzsbFbzsVdJavx4RqevWocDKe++phtzevVESUeGtt5AS\n+ZNPiG7fxttFRASKvAQEYEV99CjKLLZvj7xJ/fub33fuXDyDy5eR2jksDH1OmYIcQ1u2qM/NYiH6\n7Te8kWRmyiUob90yN2br01ZbLHju9spXMvZxSm66aPJxCg8ZBuNCypWTV3lTp7p3PFOmqGPRGyq1\nOXJatlRdCrduRa6he+9FdGleUPqw5ZOvdWOsUkU+n5Cg9tW2rXyuXDn5O5i5jX77rRBPPQUjbcWK\n1g3GRHDr1DJokPW2H3ygtsvKwlvJuHFY2VtjzBhca7EIMW2aY8/v1Cnj2wMj44zc9AiJy4Lf+4iK\nkgXGwoXuHhECqubOFaJ7d9uCMCVFiH//lY2qJUtCrWGPnTuFiIiAmmXQIPi+6/sPCBBi3TohHn3U\n+hi0id3M/Ov1240bavvp0+2312+7d6vX6/3rlS0oCN9HQVt5LDAQ390aZ8/imTrCq6+q/Q4d6tg1\nvggLfsbj2LkTq1g/P7gJZmc7dt3BgygZ2K+fLIzyyrVrQty6ZX5u7VrZu0Wrby9ZEl4s+lw6REhp\nYIY28lY/4eknmeLFkePG7M1Du2ldPK9fx6rc2sq9ShV5DEr/+s1isX7PvXvV6/WeOkRCFCtmLAlZ\nvrzc5sUXEd07dqwQ7dsj4+gDD8iTkj1SUoz3tjWh+DIs+BmPxVGBLwSMoEpSLyLkb7lwIe/3fOIJ\ndYX6xRfmbX7/HXl0Nm6EIbV2bSEaNlSF27Vr8lgiIswF2Isvwkhavjxy0uhVXNqkYkTGurn6rUQJ\nGJ71aRyEwESonbDCwiDkN22S25kleAsIgNpp40Y8V/2E8OOP8nfSXz9iBCZELe3ayW30E4GyjR/v\n+G936pTx+gcewP8NRoYFP+MVmCUn0ws1IaA/nzABXij9+qmBRkIYE3kFBdn2qbfF0aNQszz+uLmf\n+a+/GoX2a6/Jx/z8sFpWhK+1VAzaTR/4tWkTgp7KlYPu/4EHoDfv2VPtV6tKu3AB/vwVKyKQ6777\n5FQPWVl4C9PeMz4e544cMV/tE2EFr9W7nz6Nt4P69YUYMMD69+nePW/PffRoYx+PPpq3PnwBFvxM\noSc5GfpjR1b8778vC4V+/dRzK1YYhYbeRdFVmOnS09OFmDfPKPy//hopkt94wyhUtW6WYWHyRJaT\nY3Tn3LQJK3T9BKckxdu1C26a776LyNmZMxE0pUTrCgF1jPZ6JVHbnj22J6XHHjN/FuvWWb+mRg0h\nDh/O27N9+GG5jzp18na9L8CCnymU/PMPBP7kyeofeM+eWNH27Sv7tmt58klZKMTEqOfS0+UMkSNH\nFszYL140CuQHH8Rby4cfGoVf//7w4w8KUv3gAwORjnntWrwJNGuGtwgtaWnGvpYsMSZms1jwZrN/\nv+yl1LSp3K59e3jWHDwoT7JEGHdOjqzj1+b3J4LB+sYNGLrnzEH/vXtDNz9unGov0aqkiGCsfu89\nvLk0aybbFMz43//k6++/v2B+x8KMWwX/6tWrRd26dUXt2rXFVBOfvQ0bNojixYuLuLg4ERcXJ958\n803jIFjw+xzDhslCS/tHrs+Vf/489MSPP463gtWr5Wuef15un54O1YZeiLqSTZuMAnnkSHmVr3w2\nS48cFCSvgjMy1NW4Hm1un0qV8Dxu3pRTP7zyCtrOnCnfRy+Ala1KFbiqao/17Ik+srNh/3jpJSFW\nrlRVPaVLQ/+vz8BJhEmkTx+82aSlGctA6ifJiAj7z1j7VmKxmKeT8GXcJvizs7NFrVq1xIkTJ0Rm\nZqaIjY0VBw4ckNps2LBBdLej5GPB71uYecxoNyXaVAgIoZgY9VypUnANXL0aeu4PPnBtTd+rV/EG\n8sortiuHnTunCkRFsFnLZ2NtUyKap02DMA0IgMDVk5mJyNvp0+Uo6AsXoGLRehutXCnfQztG/aZP\nFvfCC+jjvffUYxUrIhHbV19hla6d0Kxty5fDTqFVYXXubGxnz/aiH1+3bo79hr6C2wT/1q1bxX33\n3fff/ttvvy3efvttqc2GDRvE/Xbe01jw+xZbtlgXGvffLwvyM2eMbbQeKK4kO1s2vlapYtt3f/Nm\nBHd17YpgL0eEovZ75ubCgKw9brEYJ5xr12Qvn+xsGGyJkFlTX/BlwgS8URCpFa7MthUrYLxu0ABv\nU1evmufxV7yAbPWl3RTf+337hHjrLSEWL0aaBm1pR43YsIrinaVsQ4Y49jv6Cs7ITaeKrZ85c4Yi\nIiL+269SpQrt2LFDamOxWGjr1q0UGxtL4eHhNGPGDIqOjjb0NVGJ7yei+Ph4io+Pd2ZojAeTloYw\n/t9/x/7o0UTDhyPsv1kzIj9N6sCyZYkqVVJztwcFyUnMMjORqmDDBuSL//hjY6IwR0lJkfPgK/tl\nyhB99RXSDIwdqyZga9OGaO1atf20acj3L4R6rHRpjFebsiEoCInJLBY5QRsRrr1+HZ+vXiXq0oVo\n+3aiqlWJlixBbvx331Xve/s2Ud++ck7/s2fxXIiILl4kKl8eBdf9/NQC65Uqoe8ePYgSEpDmYckS\n8yRtV66ofWmpXx9jTU42HiciatAAm8L48UjlIQRRaipy6ttKj/Hmm0QHDuDZNWtG9Pbb1tv6AklJ\nSZSUlOSazpyZcZYtWyaGDRv23/6XX34pnnzySanN9evXRfr/O+EmJiaKyMhIQz9ODoMpBFy9ipXq\nU0/Jel6tWsca+/Zhhdi2LcoDKmRnG2vKWvM6cYS0NLhkKn35+cFNUquy6NvXdh+nT2O8778PldHx\n4/Dm0a+KlRfjEyfklAydO6tvPNpnpWyVK+MtQ398/HgEjw0YYFSr9O2LZG9nzsjnevRAfn9H31L0\nm1INS7vVrWsegyCEsZi7oxW0rPXn6zgjN52SuNu2bZNUPVOmTDE18GqpXr26uKQrlMmC33u5fVv1\nEild2mgYtBZg5QiffWYUPK1bYzLp3VuIwYONapPr1zEJWWPjRlkvrs9oGRRke0y7d6MPbWHxV14x\njnPJEkxSinonIQGqF8Ul89YtY6CVstWvL+9r694SCdGihWpQLlJENXLfvGlUR40YYV/AK7+Z3obx\nxhvG37NBA/l5/P037DFXrhhVRfo0HitWwItICWJjbOM2wZ+VlSVq1qwpTpw4ITIyMkyNu+fPnxe5\n/z9l79ixQ1SrVs04CBb8XovWUKisorX7ZjVkHWXGDKOQmjBBrShFhEhZZcU4Y4Z6f8UL5to1rMgV\nj5obN2wLQb1g0zJhgtqufXsI2ps3jeOsUAGTg/65aCcks8lC2WJisNouW1aIevXUQC5lCwhAndwl\nS2TPofR0o/BetEjOzTNsmHFiGTQIRuQvv1QnmcaNMV599K5SYF0ICHbleVerBkO8kjKibVs5pca1\na/LvZrHANZWxjtsEvxBQ39SpU0fUqlVLTJkyRQghxIcffig+/P/3uHnz5on69euL2NhY0bJlS7FN\nqdysHQQLfq9F66NPBO8XJYf8kCGqUP7zT2R6XL3a8b5PnZLTBPTsafT/ViaX5GRzoackYouJQRKx\n3Fw5J47FAjVKdDTy4B85Yj6Wa9eM91VW3SNGqMbYSpUQn2BWYvHjj9HXkiW2J5+KFeV76ydXIvOI\nZyGEePNNtU2nTnjDOHcOz2LNGrT56y91MqhdW35runIFE6XyRvP778bnOmoUzlWtKh9/6y2onA4e\nNKbyMEvVsG6do/8TfBO3Cn5XwIL/zpKWBiFZrBhWXmfPFty9Tp2SBens2fij1+Ze2bZN9nV/913H\n+09JEeKTTxAElZxsnlJ48mSsfPXHa9aU9199FX3u2oXApDp1hJg/X77fpUvQletJTzf3b1e2n3/G\ncz9xQoiOHRHIVKOGcdVvK2Ontp3W8+n6daPb5uefW39mhw9DYNvKo3TrFgLsrMUWaOnYUb73PfdA\nn6+PIZg1y3ofubm4TmkbFZW35G6+CAt+Jk+89JL8B/nAAwV7v9RUFPW2ltNeydeubA0bmrf79lsY\nJC15Bq8AACAASURBVEeNgqrj3nshrLOyIKAiIswF5bp1ECz6vPb6wCrFj90a77+vCnetEfnTTzG5\nlSxp3aVz6VK01VcCy8+mBFppSUiQ28TG2v9dXMXJk4jGDQ2FistszK1bY+Kzxe3bUA/Nm+dYCmxf\nhwU/kycGD5b/KFu0QJRk//6u9ZHPzITOODwcaoVz58zbvf22PJ727WEkVQydQtjOBTNxIrx99Mdr\n1cLbgIJeJRIQoPq7R0TYDtj67jujSmP9evjh66N0t2+HIVs5Fhqq6u/12Tu17bQ6bmvbO++YBz7p\nbQJNmqir9ZwcBIn17Yu3Ka2XzIULsEG89571DJi5uZhsixWDykubk1/P118bx3z4sGuD7BjAgp/J\nEz//LL+GR0ern/39kR3xvvuwqlZSCbz2GgSHooe2xvnz0BFnZRmTmPXpY37N7dtC9OoFwac1NLZr\npwo5MxdGZeva1Th5aFeaigA8dEj2gOnXD6vVpCTbnj5Tp5r3vWqVeeqGzz83Hjt6FH1pU1XoN2t5\n9JWtZk3rY7xwQa0FULQovqfFggAtfX59RZV2/Tp0+Mrxtm3NBfQXX8jXW3sjEwJ2Em01se7dbddc\n3rULyeM+/pgnh7zCgp/JMzt2QDCvWycn9dJvzzxjVMUsXmze51dfqV4brVsjGlR7XVyc+XWnTllX\n03z9Ndq0aWN9jFOmQAhbO68tC7h3L7xvZs6UV843bmASMBM+WuGoFZIZGVgla4uvtGxpXnVr9Gj0\nlZ1tnr5A2bRVv2JioBePisL3/+sv27/p7dt429DGIli7xxNPmD8zs0Lo+omvTBnb4zh7Frac4cPV\n/w99+hhtCrt3y+o2XQgQYwcW/IxT6F3ytFubNsYgqSeeMO9Hn4jrqadkg+f48TBu6nn2Wev3r1cP\nueP16YzvuQe++u+8owrrGTMQQKRXydhSTQiBNyDF06hVK6MuukULub9Ro2Sj5+XLWEXPm6deGxlp\n/C5KTvlFi2wL5scew/fVhbvY5MYN27+j2TZ8uKymCg3FW4AQeKZvvYW3qbFjZePxM8/YH09OjnFB\n8d13cptJk+Tzem8lxjYs+BmnuHABwubee+Fiqf1jfP55Y81Xrd786lXVH1sf7PT++1CFvPqqnElS\nn6DVLAJUv919N1aR/frhTcWWWuDDD7HStFjkEobWqFNHvpfeq0j7tqH1U7eF3o1V2bZsgc78qaes\nV6xS3g7ygtZN09GtVy94LZUuDRXbqlVqf3rV2ZgxeEtSjNT2yMoyejl99ZXcRh813KpV3r+3L8OC\nn3Epc+dCKEyahD/gmzexWu/UCX/8CsqEEBQEvbbefU+Jyt2wQT5uscheG+fPY6VOhJXl/ffDK0V7\nTenSjo//8mWM7b77IFzsofc3//9wFCEE8u7rPXW0z8AaubnyZKds+rq1+oIoRFjtK8yfj9/ilVds\nu1Y+95zcR/Xqxjc1/TZ/PipvKfuDB6v96YPCOne2/531aFf0TZqYG48nTEBwV7t2cB9lHIcFP+MQ\nM2ciDUB4uLy6yw96L5vgYKPgnzQJhjuzFb22ypQQ0E/v2WP0rddu06Y5Nja9MdNeINAnn6jCvXp1\nTEQKL79sHIcj+YWEgEpEe13ZsvKbytatRnWIxaLGVeiNxGPGWL/XoUOqh5DFAhdTfb3fIkWQCmHU\nKKy+9RMykZwq2tpklBd27xbil1+sF75n8g8LfsYuu3fLf8ihocbi2Xnhu++MQuOtt1T9eoMG8kSg\nNZC+9BJcIbt2RVIxpY6rWc1dvVBUbATnz8PLqFEj3FeL1kVSGVdamu387wcOQNev9+7RC2+TjCNW\nSU1V0x9YLHgz0qq59HVqg4KQT19Br2Jr3Nj2/VJSEOug5OfXG2V79JDb79wpn/fzUydkxQW0Rw88\nP1vBXox7YMHP2MXMzz0lRYiPPoIfvD2PEYWMDAiE4cNlA6bikXHkCDyGnn5avlft2ph8Dh6EoNf6\nrNeoAcGyebN8jVn1qOXLIez1wVdLlqhj7N5dniyUwuKBgao7ak4O9P9t2mDs1ibB48fV8oMBAbi/\nPfbuhQC/fBnGUv1Yd+xAOyVJm7LpA+kWLpTP57WM5PHj6iRYogQSpukZP14V+nPn5q1/xr2w4Gfs\ncvWqvOru0kU25IaFQSjbQxv85eeHSWDDBpy7fRuG1ZkzjaqC+vXVPswKop8/b9R316olq226dzd3\nrSSCSkbh2jX01bu30UgZEKB64WiP2zKozpunTkL9+tk2LM+dq771VKuGRGP6sSpBcps2yQZQrW1B\nYdYs6NefeSbv6pIHH3TsO168WHAF6ZmCgwU/4xD//gvBtHAhVu6KC6Oy2cqloqD3RGnVCsbYlSvl\nIKsaNYzh+++8gz5OnpQDqerVgzDVu2x27Ajj8k8/ocpUdrYaaatXUeiNpgpmKqlTp9SkacrWurX5\n9dnZxoja77+3/nz0xcm1ZSOVNxBFj65PnaEkRFuzBmonZwOa9N9x4EDn+jPj778R3PfBB3KkNVPw\nsOBn8oVeKOn9rM3QeoHY2/RBV82bQ0U0ejQmigceQJk+RRCmpakFwGvXNn8DeeQRtb8iRZCU7eef\n5TZr1kDo9esHVZZ+XKNHG4899JAQ48bB00UrcDMyjF4933xj/fnYMk5rJx4hrEcEK1vfvs4VIVmx\nQn2jCA5GXv6vvsIbxJAhWAg4w5Ejsn//ww871x+TN1jwM/niwAGkCahSRc1Pb48zZ+Dqp3e3VFbe\n2v3775f3tSvnWrWQUXPvXuM9tEVM9GRnC7FgAd4ODh0ynj90SH4rCA+XxxAQYByn/s1kwgS5z1df\nVc/ddRfcElevhq++Pv3xunVy9K1+69pVFeZpafaDrg4cwNtOy5YYp2IfcJQ9e+Dh8/ffEPza4LaK\nFR33yzdDn/uoSBH8dnPnQvXmqN2IyR8s+BmXcfw4fN9377bf1qzyk1Z95OeHVWtsrNHFUrvpA7qc\nwSwfv37TBxZ16CDvR0cb+9W6JX78sfwdtZ44QqDNb7/JE1DRoohV6NZNLo4iBJLXmWX1tFjg8qmd\nMMuUyX+64nfeMX8e2nKWeUHvMFC2rBqPQYS3ASVHEeN6nJGbmrLWjK+zezcKlj/yCIqhL1liu/33\n3xMVLYrPVapgv0wZ9XxuLlGdOkR//EG0YIHaVs/EiUTZ2ebndu4kWrUKhbkdQQi5WHutWvL5IkWI\ncnLkY5Ury/t16xr7bdyYqGNHXK99Lrm5RF9/Lbf99lui9u3VgudEKCR/+DC+S0wMPitUrEjUqJHc\nh8WC4uIpKSiornDpEtH588bxmXHmDNF776FQfG4uUcuW8rNR2LjRsf70dOuG4ulVq+K3vXhR/l43\nbhD98kv++mYKGBdOQPnGQ4bh8zzxhLyCa97cseu0rpD6BGQdOkCXv2EDVszx8caI0qJFzQ2Z2sjP\nqChUf9Lyyy9QVSi+9xkZRh/+p5+G2iEsDCmRly83FkD59Ve4dEZEwKBsVmhFiz6t9fPP4/jFi7BL\nmLmhmm3BwfheZjaH3buhntHX3a1Xz3YE7+rVSGmxdq2c6VTJE7RihVH9pXWFVbh4Ed8zPt5+UfR/\n/rH+HdeutX0tk3+ckZseIXFZ8HsGL7wg/9HmJ0z/3DmkGGjYUBY8wcGqsTY7G22I4FtvVi0qN9fo\n/64tzq34nxNBvXDlCgKmzIRPsWJy/dZ9+6Azj4xE/h+tr76iYrGViOzff+HBVKYMsk6mpcEwbuZx\nlN9tyxY5vTERnqc2qljPvHnW1Vl+fqrt5OpVpIdu3956tTO9as5WnYb0dOOEW7IkXGmZgoMFP+MS\nrl5VPXFq1jQ3njpKerpRmGnz5uTmwrvFVqWlkiXl6xVvmsxMo0588WL0ac1YqqzKzdDnuVE2R1Mz\nCGG0dzizBQXJ3kvKdvfdtsfQtKn1PsuXd/y7CGF0S500Cce//BITZoMG8vNZv17+TbhYesHjjNxk\nHT/zHyVKEG3eTJSeTnT8uLmu21FCQoiio9X9wECiuDh132KBbrhUKet9fPqpahfo04eoXz/12pAQ\nue1vv+H4ypVEr79OFBEhny9Xzvp9rNkeLl2yfo2WmzfxzLRUrkxUvLix7bJltsdCBNvAyZPysSJF\niGbOtH2d3lbRti1RsWJE1avDLjF9OtHTTxPt2mW7HyLYKBQsFqJ27aC/f+wxoqNHifbvJ+rZE9+d\niCgyEnYEBSGIzp61fx/GTbhwAso3HjIMnyIjA5Giw4fD790aWVnwQtHr181Q/MQvXMD+6dPwj+/S\nJf+eIzdvqv0JAfdGa0VbvvlGDTCLi8Nbi58f3E+t5em5dcs8NiEqSs1Nb4+sLKOax9/fmCSNCHaJ\nxETrtXmJMJ5PP5XVNN99Zz9AKjkZKqxixeBNpY307d9f7a9IEfur8fR0IV58EXESSsDamjXGsSrl\nKnNz5aLrkZGOPz8mfzgjNz1C4rLgLzhycuBXPWwYEngpaNM1+PmZqzWuXkU6XSKoMmxNEFpf9ypV\nrNfXdRZrxbyJ5BKSRPD1t5dcTJ/SoVQpTFRPP23MIGqL7783FoAhkovTNGgAgaov0mKxIEPom2/C\n5vDLL4gRmDwZQV7TpiHXjr8/bBv5QR99PHt23vu4fFm2OzRvLhvlb91CjMXs2Xl7dkz+YMHvxXz3\nHbw08qsv1RfhVvTkes8OswRg+sjSevWs30cbwUkEHfXs2RBmw4bZ9wyxxv79SMpWoQLy7yil/PRb\nZKQQlSvLx557DgbhBx9Enp+xYxFwpa1sZauWb+3aeUtD0LateT99+2IcSj4cfcGaUaPUPlatkt8G\nPvjAaD+wl2baDL0nla1J3BbJyUjR8PbbvKJ3Nyz4vRStO2PRoo4FVenRF/AeMgTH9W6XwcHI5TJp\nkuqeqa/qVKuW9ftYU79ot6lT8z5+veulfnv6aQQm6atolSmDdMLWrqtTByUQbZV9JHIsG6fCvn1G\nTyTtc+/QAZO41m02OBhG7Lg4RLrqjbrlyhn7spUywhrHjiEdRkyMY4VkGM+HBb+XUquW/Af/wgt5\n70NfSlFJxJaaat3fvFcvtDl/Xs09ExCgFj4349dfjV44+s2eV4qe7GxjH1p1SqlS8PBZudLY7q+/\noJ+2Nxn16WN8+9FPLHkhJQWJ62zdc+FC2EKUdNHKFhdnXvhFu9Wu7Zi9hfF+nJGb7NXjwYSH2953\nhNmziYYMIWrShOiFF4jGjcPx8uWte+2sXYt/K1RA1G1SEjw6Bg60fp8OHeyPr2pVohYtiMqWJRo+\n3BhBq8csWnfQIKKoKEQWr14NbyG9l0zRokQ1ayLa1h7ffUe0fDmRv7/5+Xr17PehJTwcnlHdullv\ns3s30UMPETVoIB9PTiZ66SWi/v0RAR0ba7x2/XqikiXzNiZbCIEI4U6diCZMIMrIcF3fjAfjwgko\n33jIMDyOo0dhXC1RAkU7XJ32dv9+VHXSB9/cdRfO5+RALVGmDI4dOWK9r4wM8xVqcDD0/126GH3s\n582zP0atx03JkjAefvSRMbPka6/Bs6ZECVU9oxRbadYMdXW1AWXKVqwY3iw++wxtatTAv8WKIcNn\nflMjz5ljfdWuvDkdOCDnNho7Vu7j9m3ZM+i55/I3lryM86mnXH8PpmBwRm56hMRlwe9+PvgAwr17\nd+TLF8KY0rhVK9t9tGihtg0KklMUBwYaI1G1QVWpqUhgVqMGjJ3KJJeeDh3+K6+gDKBybc2axuAv\nrZCeNg1G1DJlkKZAYc8epGsuWhQG49WrESX7zDOYiLTRr0R4Lo5w6xb62roV+zNmyP2EhSF1xaJF\n8nUHDsBQqgSg6cnIQHDUzp2OjSOv6NVhbdsWzH0Y18OCn3GKCxeESEiAwff11+EWWbUqUghrhUJE\nhO1+Ll5EQfBBg8x9vpU0DcqbwO+/q9f262dui1C4ccPY37hxso+/gr6+cNGiSKtgxvbtsqdQxYry\ntd27239+N2/KUbPPPos3EsVt089PTjfhSXz4ofx9X3zR3SNiHIUFP+MUtnzjtf7feRUKjRvLgv7g\nQaRNfustYx5+vbuh1sVRCKhj9C6jSr+rV8ttExON7c6eldssXQo//2HDbBtT9bn5zTCr8pWWBnfH\n9eudS32RFw4dQgrs0FAkZXNUNfj++3A5nTyZq2gVJljwM05RtKh1wTdnDlQR2uAvWyxYAJVQ//5C\n/PmnECNGCDFgALJz5uQg46O/P9Q+27er12ldV/38zLM6JiYaSz8SwdNHW0j8xg1E3irn779f7mfy\nZPle+v6KF0ew1YgRxjq3O3Yg2EorzPVvN0FBtjNoFhT6SGFHbChM4YUFP2OV9euxmhs2zHo0rVLu\nUL+Fh+ctAnPtWvn6Nm3k8198IZ+vU0c+//nn0PuvX2/9HqtWmY9V73Z55QomoS+/lFexOTnGmAN9\nJssGDczv/dVX6kRRtKgQ27bheG4uVthEUBvp9fh3Cn3Mw0svuWcczJ2BBT9jyoEDcg6ZuDjzdleu\nQDffurW8As6r4NBXeCpWTD6vN3iWKpX372QtOtbRFAQDBxqvTUhQhX+RIkL88Yf5tfoV9bBh8vnU\n1DsTzZqdDfXMc8+pk48QcrH6kBDr34PxDljwM6boV9hE8JKxxvDhclvFrVNPUhKE+JYtUIUo+XB2\n7pSDwpRAMIWTJ1GeTzk/YAA8a0JChJg40fxeek8XsxQLjRvbrtOrcOmS8dqOHfFGkJmJZHS2VDTd\nu8vX2kr1XJCMGqWOITBQ9vj54Qfk2D9wwD1jY+4cLPgZU/bvlz1WYmJst58yRRZsAwYY2yxZIkfP\nWiwQ3EuXwrtlzRqsoF95xXySSU6GWqRxY2Pend9+k+9TogRUKtOn41h6OqJdzTJhau0FCtOn463D\n3x/un9u3G+0ZW7Y49iz//RexAorXT/v2auWvO40+HsHapMl4Nyz4GaskJsK4+cgjELq2yMgQYuhQ\n6MC7dIHqQkERcvocP3o9eUiIEMuWWb/H99+bX0+kXnf5slG4799vfCPRbjNmyPfZtMnYJjISHjgl\nSmDSefllx57htWtIlaD006mTuc/9nUIfCPfVV+4bC+M+WPAzBcbZszB2KsZYbV53a1toqPV0yC+9\nZH6NNiDrxAnj+V9/RZZOa/f85Rf5PmZqruBg9XxeInIdcQ81Y/t2vLnYq+GbV06dwuQTGen45MV4\nH87IzYA7mR6C8Qxyc4k2bkR+mrZtUWHJGhMnotoSEdGRI0Q1ahD5+cnVlvSkp6OKlFllq1at5P2W\nLYkefRQVtj7/HHls2rUj6tyZaM0atImNRY6fdu2I9u6V+woMJBo8mKhjR7nfjh2JSpcmunxZPfbw\nw+pnPztZqvbsITp2jKh1a6JKleRzoaGoVmaL998nevJJfC5blmj7dqJatWxf4yhVqxL9/LNr+mJ8\nFBdOQPnGQ4bhE+TkyEbKQYOstz10CGkU9AZf/ep3wQLZb94st7+WxYuF6N0baRKUiFqtRwoRUiUs\nXgyfecVTJjMT/v4DBuC4PY4fR+GSnj0ROevoKv/TT1U7RunSeA6zZ+NzlSpwKbWHNl0FESKiGcaV\nOCM3PULisuC/c+zcaRTchw8b2yUkqOcVT52gIPjFayNoa9WCQL52DUFeZoFXjqAvf/jAA859T2fQ\nV/JyJHpXy9atCALT9qFPQcEwzuKM3GRVjxMIQfTBB0R//om0tv37u3tE9jFTvwQFyfu7dxMtWqTu\nZ2cTzZtHdPfdSIlcpw7RrFno6/XXoW4JDCQaMCD/44qLQ/pnhUaN8t+Xs+jVOGZF062Rmgo11fXr\n6rGOHYlGjnTN2BjGJbhwAso3HjKMPPPaa/KqzlahEk9iwgSM12JR3R0fe0xVhZi9FZw4UbBjunUL\naYlbt4bB0l6t3IJkzx7VZbJdO6SAcJTNm43P7q+/Cm6sjO/ijNy0/H8HbsVisZAHDCPPNG9OtHOn\nup+QQPTpp+4bT164cIGoWTOiU6fUY4sXo9CJEDCELlmC42PGEM2d655xuovcXBSCsWfE1XPpEt6K\n/v0X+1WrEh08SBQS4voxMr6NM3KTVT1OkJ0t79urKOVJlC9PdOWKfEwRVhYL0VdfoSJTQABR/fqO\n93vqFNHZs1DdmKmVCgt+fnkX+kSonLVhA9E77+DZvfwyC33G82DB7wR6l0B7LoKexqhRRFOn4nOF\nCkR9+8rnzUr/2WLJErhWZmcTRUcT/fYbUalSrhlrYaJ+fbimMoynUshElWehN4oGB7tnHPnl7beJ\nEhOJFi6E33pEhHP9vfCC+hZ04EDhUXsxjK/BK34n0Kt6MjPdMw5n6NLFdX0V9jcghvEVnPrTXLNm\nDdWrV48iIyNp2rRppm3Gjh1LkZGRFBsbS3u1YZdegH6FHB7unnF4CrNnq289TZoQDRvm3vEwDGNO\nvr16cnJyqG7duvTLL79QeHg4NW3alL7++muKior6r01iYiLNmzePEhMTaceOHTRu3Djavn27cRCF\n1KvnzBn4rv/5J9E990DH7euGvH//hcdQnTrw7WcYpmBwi1fPzp07qXbt2lS9enUiIho4cCD98MMP\nkuBfuXIlDR48mIiImjdvTlevXqXU1FSqUKFCfm/rUYSHE23Z4u5ReBblymFjGMZzybfgP3PmDEVo\ndB1VqlShHTt22G2TkpJiKvgnTpz43+f4+HiKj4/P79AYhmG8jqSkJErShrc7Qb4Fv8VWSkcN+lcR\na9dpBT/DMAwjo18QT5o0Kd995du4Gx4eTsnJyf/tJycnU5UqVWy2SUlJoXBft4AyDMO4mXwL/rvu\nuouOHj1KJ0+epMzMTPr222+pR48eUpsePXrQF198QURE27dvp5IlS3qNfp9hGKawkm9VT0BAAM2b\nN4/uu+8+ysnJoaFDh1JUVBQtWLCAiIhGjBhBXbt2pcTERKpduzaFhobSIm3KR4ZhGMYtcJI2hmGY\nQogzcpNjKxmGYXwMFvwMwzA+Bgt+hmEYH4MFP8MwjI/Bgp9hGMbHYMHPMAzjY7DgZxiG8TFY8DMM\nw/gYLPgZhmF8DBb8DMMwPgYLfoZhGB+DBT/DMIyPwYKfYRjGx2DBzzAM42Ow4GcYhvExWPAzDMP4\nGCz4GYZhfAwW/AzDMD4GC36GYRgfgwU/wzCMj8GCn2EYxsdgwc8wDONjsOBnGIbxMVjwMwzD+Bgs\n+BmGYXwMFvwMwzA+Bgt+hmEYH4MFP8MwjI/Bgp9hGMbHYMHPMAzjY7DgZxiG8TFY8DMMw/gYLPgZ\nhmF8DBb8DMMwPgYLfoZhGB+DBT/DMIyPwYKfYRjGx2DBzzAM42Ow4GcYhvExWPAz/9fe/YU09Ydx\nHP8M80IwzOW/5QRzumqb2wJrGVjJWpGFVEoIFRYxIiKwC6noom6yRVfSjTcW0p+LKMjAjCKUQo2B\nGwYWFbVy/pksN9EUatLzu5BEf9vc8WTnLPa87ua+4NuD30e3c44yxhIMD37GGEswPPgZYyzB8OBn\njLEEw4OfMcYSDA9+xhhLMDz4GWMswfDg/0OdnZ1yJ/wR7pcX98vrX+8XS/TgDwQCsNls0Gq12LVr\nF8bHxyOuy8/Ph9FoxMaNG7F582bRofHqX//G4X55cb+8/vV+sUQPfofDAZvNhg8fPsBqtcLhcERc\np1Ao0NnZCbfbDafTKTqUMcbY8hA9+B8/foza2loAQG1tLR49ehR1LRGJ/TSMMcaWmYJETuX09HQE\ng0EAs4NdqVTOPZ6voKAAaWlpSEpKwsmTJ2G328MjFAoxCYwxltDE/lK9YrEnbTYbfD5f2MevXLmy\n4LFCoYg6vLu6uqBSqeD3+2Gz2bB+/XqUlZUtWMOvCBhjTDqLDv7nz59HfS47Oxs+nw85OTkYGRlB\nVlZWxHUqlQoAkJmZiQMHDsDpdIYNfsYYY9IR/R5/ZWUlWlpaAAAtLS3Yv39/2Jrp6WlMTk4CAKam\npvDs2TMUFxeL/ZSMMcaWgej3+AOBAA4dOoSBgQHk5+fj/v37WLVqFYaHh2G329HW1obPnz/j4MGD\nAICZmRkcPnwYFy5cWNYvgDHG2BKRDMbGxmjnzp1UVFRENpuNgsFg2JqBgQHasWMH6XQ60uv11NjY\nKEPpQu3t7bRu3ToqLCwkh8MRcc2ZM2eosLCQjEYjuVwuiQsXF6v/zp07ZDQaqbi4mLZu3Up9fX0y\nVEYm5NgTETmdTkpKSqKHDx9KWBebkP6Ojg4ym82k1+tp+/bt0gbGEKvf7/fT7t27yWQykV6vp1u3\nbkkfGcXx48cpKyuLDAZD1DXxvG9j9YvZt7IM/vr6erp27RoRETkcDjp37lzYmpGREXK73URENDk5\nSVqtlt6+fStp53wzMzOk0WjI4/HQz58/yWQyhfW0tbXRnj17iIjo9evXZLFY5EiNSEh/d3c3jY+P\nE9HsRo+XfiHtv9eVl5fT3r176cGDBzKURiakPxgMkk6nI6/XS0SzgzReCOm/dOkSnT9/nohm25VK\nJYVCITlyw7x8+ZJcLlfUwRnP+5Yodr+YfSvLn2wQcg9ATk4OzGYzACA1NRUbNmzA8PCwpJ3zOZ1O\nFBYWIj8/H8nJyaipqUFra+uCNfO/LovFgvHxcYyOjsqRG0ZIf2lpKdLS0gDM9g8ODsqRGkZIOwDc\nuHED1dXVyMzMlKEyOiH99+7dQ1VVFdRqNQAgIyNDjtSIhPSrVCpMTEwAACYmJrB69WqsWLHotSOS\nKSsrQ3p6etTn43nfArH7xexbWQb/6OgosrOzAcxeHRTrIH/58gVutxsWi0WKvIiGhoaQl5c391it\nVmNoaCjmmngZnkL652tubkZFRYUUaTEJPfatra04deoUgPi6N0RI/8ePHxEIBFBeXo6SkhLcvn1b\n6syohPTb7Xb09/djzZo1MJlMaGxslDpTtHjet0sldN/+tR/Jy3EPAAB8//4d1dXVaGxsRGpq6rJ3\nCiV0kND/zpXHywBaSkdHRwdu3ryJrq6uv1gknJD2uro6OBwOKBQK0OxbmBKUCSOkPxQKweVyeLOv\nKwAAAkhJREFU4cWLF5ienkZpaSm2bNmCoqIiCQoXJ6S/oaEBZrMZnZ2d+PTpE2w2G/r6+rBy5UoJ\nCv9cvO7bpVjKvv1rg3857gEIhUKoqqrCkSNHIl4uKqXc3Fx4vd65x16vd+5lebQ1g4ODyM3Nlaxx\nMUL6AeDNmzew2+14+vTpoi8vpSSkvbe3FzU1NQCAb9++ob29HcnJyaisrJS0NRIh/Xl5ecjIyEBK\nSgpSUlKwbds29PX1xcXgF9Lf3d2NixcvAgA0Gg3Wrl2L9+/fo6SkRNJWMeJ53wq15H27bGcglqC+\nvn7uyoCrV69GPLn769cvOnr0KNXV1UmdF1EoFKKCggLyeDz048ePmCd3e3p64uokkZD+r1+/kkaj\noZ6eHpkqIxPSPt+xY8fi6qoeIf3v3r0jq9VKMzMzNDU1RQaDgfr7+2UqXkhI/9mzZ+ny5ctEROTz\n+Sg3N5fGxsbkyI3I4/EIOrkbb/v2t8X6xexb2S7ntFqtYZdzDg0NUUVFBRERvXr1ihQKBZlMJjKb\nzWQ2m6m9vV2O3DlPnjwhrVZLGo2GGhoaiIioqamJmpqa5tacPn2aNBoNGY1G6u3tlSs1olj9J06c\nIKVSOXe8N23aJGfuAkKO/W/xNviJhPVfv36ddDodGQyGuLh8eb5Y/X6/n/bt20dGo5EMBgPdvXtX\nztwFampqSKVSUXJyMqnVampubv6n9m2sfjH7VvQNXIwxxv5N/B+4GGMswfDgZ4yxBMODnzHGEgwP\nfsYYSzA8+BljLMHw4GeMsQTzH2lzdW76BQhrAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x7fbe390>"
]
}
],
"prompt_number": 89
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Hmm, there's at least some signal there. How does spectral embedding do with 2D?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"embed = manifold.SpectralEmbedding(n_components=2)\n",
"results3=embed.fit(coords)\n",
"coords3=results3.embedding_\n",
"d = distCompare(dist_mat,coords3)\n",
"scatter([x for x,y in d],[y for x,y in d],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 90,
"text": [
"<matplotlib.collections.PathCollection at 0x7c8af50>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAFtCAYAAAAAmAHJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x7045450>"
]
}
],
"prompt_number": 90
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Not so hot..."
]
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Look at stress vs dimension"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We're able to do a reasonable job of embedding into 20 dimensions with MDS. 10 even looks somewhat ok. Let's look at behavior of the residual stress as a function of dimension:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"vs={}\n",
"for nComps in (140,120,100,80,60,40,20,10,5,2):\n",
" mds3 = manifold.MDS(n_components=nComps, random_state=3, dissimilarity=\"precomputed\",n_jobs = 4, verbose=0,max_iter=1000)\n",
" results3 = mds3.fit(dist_mat)\n",
" print 'Final stress at dim=%d:'%nComps,results3.stress_,'stress per element:',results3.stress_/len(dist_mat)\n",
" vs[nComps]=results3.stress_/len(dist_mat)\n",
"scatter(vs.keys(),vs.values(),edgecolors='none')\n",
"yscale('log')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=140: 12.7282381352 stress per element: 0.0417319283121\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=120: 13.3666602299 stress per element: 0.0438251155077\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=100: 13.90154979 stress per element: 0.0455788517704\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=80: 15.1409945495 stress per element: 0.0496426050802\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=60: 17.844384297 stress per element: 0.058506178023\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=40: 25.7793697019 stress per element: 0.0845225236129\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=20: 83.6518627219 stress per element: 0.274268402367\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=10: 306.257420455 stress per element: 1.00412269001\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=5: 979.602872762 stress per element: 3.21181269758\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=2: 4082.51507338 stress per element: 13.3852953225\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAFxCAYAAACbTqgXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n7AFUAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x598a1d0>"
]
}
],
"prompt_number": 91
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Yeah, the stress is going up exponentially with dimension. These data really don't want to be in a 2D space.\n",
"\n",
"Try non-metric embedding"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"vs={}\n",
"for nComps in (140,120,100,80,60,40,20,10,5,2):\n",
" mds3 = manifold.MDS(metric=False,n_components=nComps,random_state=3, dissimilarity=\"precomputed\",n_jobs = 4, verbose=0,max_iter=1000)\n",
" results3 = mds3.fit(dist_mat)\n",
" print 'Final stress at dim=%d:'%nComps,results3.stress_,'stress per element:',results3.stress_/len(dist_mat)\n",
" vs[nComps]=results3.stress_/len(dist_mat)\n",
"scatter(vs.keys(),vs.values(),edgecolors='none')\n",
"yscale('log')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=140: 20.8713016229 stress per element: 0.0684304971242\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=120: 24.3989596423 stress per element: 0.0799965889911\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=100: 28.7286560841 stress per element: 0.0941923150298\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=80: 36.0835726625 stress per element: 0.118306795615\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=60: 47.6762604743 stress per element: 0.156315608112\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=40: 71.9307458185 stress per element: 0.23583851088\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=20: 151.843304144 stress per element: 0.497846898833\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=10: 328.574341064 stress per element: 1.07729292152\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=5: 742.142966121 stress per element: 2.43325562663\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=2: 2092.47228189 stress per element: 6.86056485866\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAFxCAYAAACbTqgXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJQyTH3W74a4AAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x65f9e10>"
]
}
],
"prompt_number": 92
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"helps somewhat at lower dimension, but not dramatically. Plus it's a lot slower"
]
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"A larger data set"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Maybe it's possible to do better with a larger data set? This seems unlikely, but we can at least try:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"assays = data2[['assay_chemblid','target_chemblid']].groupby('assay_chemblid').count()\n",
"print assays.shape\n",
"goodassays = assays.ix[(assays.assay_chemblid >= 10)&(assays.assay_chemblid <= 15)]\n",
"subset = data2.ix[data.assay_chemblid.isin(list(goodassays.index))]\n",
"print subset.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(108, 2)\n",
"(708, 18)\n"
]
}
],
"prompt_number": 93
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mols = subset[['parent_cmpd_chemblid','name_in_reference','SMILES', 'ROMol', 'assay_chemblid']]\n",
"print mols.shape\n",
"fps = [Chem.GetMorganFingerprintAsBitVect(m,2,nBits=2048) for m in mols['ROMol']]\n",
"dist_mat = []\n",
"for i,fp in enumerate(fps):\n",
" dist_mat.append(DataStructs.BulkTanimotoSimilarity(fps[i],fps,returnDistance=1))\n",
"dist_mat=numpy.array(dist_mat) \n",
"print dist_mat.shape "
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(708, 5)\n",
"(708, 708)"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
}
],
"prompt_number": 94
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"vs={}\n",
"for nComps in (140,120,100,80,60,40,20,10,5,2):\n",
" mds3 = manifold.MDS(n_components=nComps, random_state=3, dissimilarity=\"precomputed\",n_jobs = 4, verbose=0,max_iter=1000)\n",
" results3 = mds3.fit(dist_mat)\n",
" print 'Final stress at dim=%d:'%nComps,results3.stress_,'stress per element:',results3.stress_/len(dist_mat)\n",
" vs[nComps]=results3.stress_/len(dist_mat)\n",
"scatter(vs.keys(),vs.values(),edgecolors='none')\n",
"yscale('log')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=140: 67.2404191613 stress per element: 0.0949723434482\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=120: 72.2944675787 stress per element: 0.102110829913\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=100: 79.2412581743 stress per element: 0.111922681037\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=80: 92.3713903258 stress per element: 0.130468065432\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=60: 119.625068295 stress per element: 0.168961960869\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=40: 210.430766815 stress per element: 0.297218597196\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=20: 695.428536708 stress per element: 0.982243695916\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=10: 2221.46528359 stress per element: 3.13766282992\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=5: 6433.47666107 stress per element: 9.08683144219\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=2: 24611.8646668 stress per element: 34.7625207159\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAFxCAYAAACbTqgXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x6601d10>"
]
}
],
"prompt_number": 95
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nope, that definitely made things worse."
]
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"and larger still"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"assays = data2[['assay_chemblid','target_chemblid']].groupby('assay_chemblid').count()\n",
"print assays.shape\n",
"goodassays = assays.ix[(assays.assay_chemblid >= 10)&(assays.assay_chemblid <= 18)]\n",
"subset = data2.ix[data.assay_chemblid.isin(list(goodassays.index))]\n",
"print subset.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(108, 2)\n",
"(1045, 18)\n"
]
}
],
"prompt_number": 96
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mols = subset[['parent_cmpd_chemblid','name_in_reference','SMILES', 'ROMol', 'assay_chemblid']]\n",
"print mols.shape\n",
"fps = [Chem.GetMorganFingerprintAsBitVect(m,2,nBits=2048) for m in mols['ROMol']]\n",
"dist_mat = []\n",
"for i,fp in enumerate(fps):\n",
" dist_mat.append(DataStructs.BulkTanimotoSimilarity(fps[i],fps,returnDistance=1))\n",
"dist_mat=numpy.array(dist_mat) \n",
"print dist_mat.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(1045, 5)\n",
"(1045, 1045)"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
}
],
"prompt_number": 97
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"vs={}\n",
"for nComps in (140,120,100,80,60,40,20,10,5,2):\n",
" mds3 = manifold.MDS(n_components=nComps, random_state=3, dissimilarity=\"precomputed\",n_jobs = 4, verbose=0,max_iter=1000)\n",
" results3 = mds3.fit(dist_mat)\n",
" print 'Final stress at dim=%d:'%nComps,results3.stress_,'stress per element:',results3.stress_/len(dist_mat)\n",
" vs[nComps]=results3.stress_/len(dist_mat)\n",
"scatter(vs.keys(),vs.values(),edgecolors='none')\n",
"yscale('log')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=140: 139.380840274 stress per element: 0.13337879452\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=120: 150.191914066 stress per element: 0.143724319681\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=100: 166.888061149 stress per element: 0.159701493923\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=80: 201.13751144 stress per element: 0.192476087502\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=60: 269.966764269 stress per element: 0.258341401215\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=40: 485.941068467 stress per element: 0.465015376524\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=20: 1618.41731942 stress per element: 1.54872470758\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=10: 5047.57853434 stress per element: 4.83021869315\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=5: 14296.8251973 stress per element: 13.6811724377\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=2: 53646.5018092 stress per element: 51.3363653677\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAFxCAYAAACbTqgXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niPIHAAtR/gBgIcofACz0f5/NvZMj1bJlAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x68bb6d0>"
]
}
],
"prompt_number": 98
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Continuing to get worse."
]
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Try less data"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"assays = data2[['assay_chemblid','target_chemblid']].groupby('assay_chemblid').count()\n",
"print assays.shape\n",
"goodassays = assays.ix[assays.assay_chemblid == 15]\n",
"subset = data2.ix[data.assay_chemblid.isin(list(goodassays.index))]\n",
"print subset.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(108, 2)\n",
"(120, 18)\n"
]
}
],
"prompt_number": 99
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mols = subset[['parent_cmpd_chemblid','name_in_reference','SMILES', 'ROMol', 'assay_chemblid']]\n",
"print mols.shape\n",
"fps = [Chem.GetMorganFingerprintAsBitVect(m,2,nBits=2048) for m in mols['ROMol']]\n",
"dist_mat = []\n",
"for i,fp in enumerate(fps):\n",
" dist_mat.append(DataStructs.BulkTanimotoSimilarity(fps[i],fps,returnDistance=1))\n",
"dist_mat=numpy.array(dist_mat) \n",
"print dist_mat.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(120, 5)\n",
"(120, 120)\n"
]
}
],
"prompt_number": 100
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"vs={}\n",
"for nComps in (140,120,100,80,60,40,20,10,5,2):\n",
" mds3 = manifold.MDS(n_components=nComps, random_state=3, dissimilarity=\"precomputed\",n_jobs = 4, verbose=0,max_iter=1000)\n",
" results3 = mds3.fit(dist_mat)\n",
" print 'Final stress at dim=%d:'%nComps,results3.stress_,'stress per element:',results3.stress_/len(dist_mat)\n",
" vs[nComps]=results3.stress_/len(dist_mat)\n",
"scatter(vs.keys(),vs.values(),edgecolors='none')\n",
"yscale('log')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=140: 2.56157223214 stress per element: 0.0213464352678\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=120: 2.57821067766 stress per element: 0.0214850889805\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=100: 2.65583739686 stress per element: 0.0221319783072\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=80: 2.73926053033 stress per element: 0.0228271710861\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=60: 2.92796261185 stress per element: 0.0243996884321\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=40: 3.45058526213 stress per element: 0.0287548771845\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=20: 6.51584911558 stress per element: 0.0542987426298\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=10: 23.1791703087 stress per element: 0.193159752572\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=5: 96.7566944154 stress per element: 0.806305786795\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Final stress at dim=2: 536.317416776 stress per element: 4.46931180647\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAFxCAYAAACbTqgXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhYg/AFiI+AOAhYg/AFjo/wB/hYMQ3a9s6wAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x7ec7190>"
]
}
],
"prompt_number": 101
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"That's a lot less stress per point than before, but it's still pretty high. Look at the distances to be sure:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mds3 = manifold.MDS(n_components=2, random_state=3, dissimilarity=\"precomputed\",n_jobs = 4, verbose=0,max_iter=1000)\n",
"results3 = mds3.fit(dist_mat)\n",
"coords3=results3.embedding_\n",
"d = distCompare(dist_mat,coords3)\n",
"scatter([x for x,y in d],[y for x,y in d],edgecolors='none')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 102,
"text": [
"<matplotlib.collections.PathCollection at 0x5ca6f50>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAFtCAYAAAAAmAHJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x5ca2550>"
]
}
],
"prompt_number": 102
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment